subject:( en NATURAL LANGUAGE PROCESSING)

Anna University

1. Balaji J. Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages;.

Degree: Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages, 2015, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/35514

►

This thesis attempts to tackle Natural Language Processing NLP tasks by exploiting the special characteristics of morphologically rich newlineLanguages In this thesis we use Tamil… (more)

Subjects/Keywords: Natural Language Processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

J, B. (2015). Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/35514

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

J, Balaji. “Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages;.” 2015. Thesis, Anna University. Accessed January 21, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/35514.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

J, Balaji. “Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages;.” 2015. Web. 21 Jan 2021.

Vancouver:

J B. Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages;. [Internet] [Thesis]. Anna University; 2015. [cited 2021 Jan 21]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/35514.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

J B. Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages;. [Thesis]. Anna University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/35514

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

2. PEDRO HENRIQUE THOMPSON FURTADO. [en] AUTOMATIC INTERPRETATION OF EQUIPMENT OPERATION REPORTS.

Degree: 2017, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30732

►

[pt] As unidades operacionais da área de Exploração e Produção (EeP) da PETROBRAS utilizam relatórios diários para o registro de situações e eventos em Unidades… (more)

▼

[pt] As unidades operacionais da área de Exploração e Produção (EeP) da PETROBRAS utilizam relatórios diários para o registro de situações e eventos em Unidades Estacionárias de Produção (UEPs), as conhecidas plataformas de produção de petróleo. Um destes relatórios, o SITOP (Situação Operacional das Unidades Marítimas), é um documento diário em texto livre que apresenta informações numéricas (índices de produção, algumas vazões, etc.) e, principalmente, informações textuais. A parte textual, apesar de não estruturada, encerra uma valiosíssima base de dados de histórico de eventos no ambiente de produção, tais como: quebras de válvulas, falhas em equipamentos de processo, início e término de manutenções, manobras executadas, responsabilidades etc. O valor destes dados é alto, mas o custo da busca de informações também o é, pois se demanda a atenção de técnicos da empresa na leitura de uma enorme quantidade de documentos. O objetivo do presente trabalho é o desenvolvimento de um modelo de processamento de linguagem natural para a identificação, nos textos dos SITOPs, de entidades nomeadas e extração de relações entre estas entidades, descritas formalmente em uma ontologia de domínio aplicada a eventos em unidades de processamento de petróleo e gás em ambiente offshore. Ter-se-á, portanto, um método de estruturação automática da informação presente nestes relatórios operacionais. Os resultados obtidos demonstram que a metodologia é útil para este caso, ainda que passível de melhorias em diferentes frentes. A extração de relações apresenta melhores resultados que a identificação de entidades, o que pode ser explicado pela diferença entre o número de classes das duas tarefas. Verifica-se também que o aumento na quantidade de dados é um dos fatores mais importantes para a melhoria do aprendizado e da eficiência da metodologia como um todo.

[en] The operational units at the Exploration and Production (E and P) area at PETROBRAS make use of daily reports to register situations and events from their Stationary Production Units (SPUs), the well-known petroleum production platforms. One of these reports, called SITOP (the Portuguese acronym for Offshore Unities Operational Situation), is a daily document in free text format that presents numerical information and, mainly, textual information about operational situation of offshore units. The textual section, although unstructured, stores a valuable database with historical events in the production environment, such as: valve breakages, failures in processing equipment, beginning and end of maintenance activities, actions executed, responsibilities, etc. The value of these data is high, as well as the costs of searching relevant information, consuming many hours of attention from technicians and engineers to read the large number of documents. The goal of this dissertation is to develop a model of natural language processing to recognize named entities and extract relations among them, described formally as a domain ontology applied to events in offshore oil and gas…

Advisors/Committee Members: HELIO CORTES VIEIRA LOPES.

Subjects/Keywords: [pt] GAS NATURAL; [en] NATURAL GAS; [pt] PETROLEO; [en] PETROLEUM; [pt] ONTOLOGIAS; [en] ONTOLOGIES; [pt] APRENDIZADO AUTOMATICO; [en] AUTOMATIC LEARNING; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

FURTADO, P. H. T. (2017). [en] AUTOMATIC INTERPRETATION OF EQUIPMENT OPERATION REPORTS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30732

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

FURTADO, PEDRO HENRIQUE THOMPSON. “[en] AUTOMATIC INTERPRETATION OF EQUIPMENT OPERATION REPORTS.” 2017. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30732.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

FURTADO, PEDRO HENRIQUE THOMPSON. “[en] AUTOMATIC INTERPRETATION OF EQUIPMENT OPERATION REPORTS.” 2017. Web. 21 Jan 2021.

Vancouver:

FURTADO PHT. [en] AUTOMATIC INTERPRETATION OF EQUIPMENT OPERATION REPORTS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2017. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30732.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

FURTADO PHT. [en] AUTOMATIC INTERPRETATION OF EQUIPMENT OPERATION REPORTS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2017. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30732

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

3. Doval, Yerai. Seeking robustness in a multilingual world: from pipelines to embeddings .

Degree: 2019, Universidad da Coruña

URL: http://hdl.handle.net/2183/24535

► [Abstract] In this dissertation, we study two approaches to overcome the challenges posed by processing user-generated non-standard multilingual text content as it is found on… (more)

Subjects/Keywords: Procesamiento en lenguaje natural (Informática); Ensamblado de palabras; Natural language processing; Word segmentation

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Doval, Y. (2019). Seeking robustness in a multilingual world: from pipelines to embeddings . (Doctoral Dissertation). Universidad da Coruña. Retrieved from http://hdl.handle.net/2183/24535

Chicago Manual of Style (16^th Edition):

Doval, Yerai. “Seeking robustness in a multilingual world: from pipelines to embeddings .” 2019. Doctoral Dissertation, Universidad da Coruña. Accessed January 21, 2021. http://hdl.handle.net/2183/24535.

MLA Handbook (7^th Edition):

Doval, Yerai. “Seeking robustness in a multilingual world: from pipelines to embeddings .” 2019. Web. 21 Jan 2021.

Vancouver:

Doval Y. Seeking robustness in a multilingual world: from pipelines to embeddings . [Internet] [Doctoral dissertation]. Universidad da Coruña; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/2183/24535.

Council of Science Editors:

Doval Y. Seeking robustness in a multilingual world: from pipelines to embeddings . [Doctoral Dissertation]. Universidad da Coruña; 2019. Available from: http://hdl.handle.net/2183/24535

4. Alkhazi, Ibrahim. Compression-based parts-of-speech tagger for the Arabic language.

Degree: PhD, 2019, Bangor University

URL: https://research.bangor.ac.uk/portal/en/theses/compressionbased-partsofspeech-tagger-for-the-arabic-language(076552a6-32ee-41ff-9255-7abc6489c010).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.801316

► The Arabic language is a morphologically complex language that causes various difficulties for various NLP systems, such as POS tagging. The motive of this research… (more)

▼ The Arabic language is a morphologically complex language that causes various difficulties for various NLP systems, such as POS tagging. The motive of this research is to investigate the development and training of a compression-based Arabic POS tagger using the PPM algorithm. The adoption of the algorithm for Arabic POS tagging may increase the efficiency and reduce the Arabic language ambiguity problem. The best text compression algorithms can be applied to NLP tasks often with state-of-the-art results. This research examines the use of tag-based compression of larger Arabic resources to re-evaluate the performance of tag-based compression which may reveal POS linguistic aspects of the Arabic language. We also found that tag-based text compression for the Arabic text can be utilised as a means of evaluating the performance and quality of the Arabic POS taggers. The results of the experiments show that the tag-based compression of the text can effectively be used for assessing the performance of Arabic POS taggers when used to tag different types of the Arabic text, and also as a means of comparing the performance of two Arabic POS taggers on the same text. With the rapid growth of Arabic text on the Web, studies that address the problems of classification and segmentation of the Arabic language are limited compared to other languages, most of which implement word-based and feature extraction algorithms. This research adopts a PPM character-based compression scheme to classify and segment Classical Arabic (CA) and Modern Standard Arabic (MSA) texts. An initial experiment using the PPM classification method on samples of text resulted in an accuracy of 95.5%, an average precision of 0.958, an average recall of 0.955 and an average F-measure of 0.954, using the concept of minimum cross-entropy. Segmenting the CA and MSA text using the PPM compression algorithm obtained an accuracy of 86%, an average precision of 0.869, an average recall of 0.86 and an average F-measure of 0.859. This research describes the creation of the new Bangor Arabic Annotated Corpus (BAAC) which is a Modern Standard Arabic (MSA) corpus that comprises 50K words manually annotated by parts-of-speech. For evaluating the quality of the corpus, the Kappa coefficient and a direct percent agreement for each tag were calculated for the new corpus and a Kappa value of 0.956 was obtained, with an average observed agreement of 94.25%. The corpus was used to evaluate the widely used Madamira Arabic POS tagger and to further investigate compression models for text compressed using POS tags. Also, a new annotation tool was developed and employed for the annotation process of the BAAC.

Subjects/Keywords: Language modelling; natural language processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Alkhazi, I. (2019). Compression-based parts-of-speech tagger for the Arabic language. (Doctoral Dissertation). Bangor University. Retrieved from https://research.bangor.ac.uk/portal/en/theses/compressionbased-partsofspeech-tagger-for-the-arabic-language(076552a6-32ee-41ff-9255-7abc6489c010).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.801316

Chicago Manual of Style (16^th Edition):

Alkhazi, Ibrahim. “Compression-based parts-of-speech tagger for the Arabic language.” 2019. Doctoral Dissertation, Bangor University. Accessed January 21, 2021. https://research.bangor.ac.uk/portal/en/theses/compressionbased-partsofspeech-tagger-for-the-arabic-language(076552a6-32ee-41ff-9255-7abc6489c010).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.801316.

MLA Handbook (7^th Edition):

Alkhazi, Ibrahim. “Compression-based parts-of-speech tagger for the Arabic language.” 2019. Web. 21 Jan 2021.

Vancouver:

Alkhazi I. Compression-based parts-of-speech tagger for the Arabic language. [Internet] [Doctoral dissertation]. Bangor University; 2019. [cited 2021 Jan 21]. Available from: https://research.bangor.ac.uk/portal/en/theses/compressionbased-partsofspeech-tagger-for-the-arabic-language(076552a6-32ee-41ff-9255-7abc6489c010).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.801316.

Council of Science Editors:

Alkhazi I. Compression-based parts-of-speech tagger for the Arabic language. [Doctoral Dissertation]. Bangor University; 2019. Available from: https://research.bangor.ac.uk/portal/en/theses/compressionbased-partsofspeech-tagger-for-the-arabic-language(076552a6-32ee-41ff-9255-7abc6489c010).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.801316

Pontifical Catholic University of Rio de Janeiro

5. CARLOS EDUARDO MEGER CRESTANA. [en] A TOKEN CLASSIFICATION APPROACH TO DEPENDENCY PARSING.

Degree: 2010, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16458

►

[pt] Uma das tarefas mais importantes em Processamento de Linguagem Natural é a análise sintática, onde a estrutura de uma sentença é determinada de acordo… (more)

▼

[pt] Uma das tarefas mais importantes em Processamento de Linguagem Natural é a análise sintática, onde a estrutura de uma sentença é determinada de acordo com uma dada gramática, informando o significado de uma sentença a partir do significado das palavras nela contidas. A Análise Sintática baseada em Gramáticas de Dependência consiste em identificar para cada palavra a outra palavra na sentença que a governa. Assim, a saída de um analisador sintático de dependência é uma árvore onde os nós são as palavras da sentença. Esta estrutura simples, mas rica, é utilizada em uma grande variedade de aplicações, entre elas Sistemas de Pergunta-Resposta, Tradução Automática, Extração de Informação, e Identificação de Papéis Semânticos. Os sistemas estado-da-arte em análise sintática de dependência utilizam modelos baseados em transições ou modelos baseados em grafos. Essa dissertação apresenta uma abordagem por classificação tokena- token para a análise sintática de dependência ao criar um conjunto especial de classes que permitem a correta identificação de uma palavra na sentença. Usando esse conjunto de classes, qualquer algoritmo de classificação pode ser treinado para identificar corretamente a palavra governante de cada palavra na sentença. Além disso, este conjunto de classes permite tratar igualmente relações de dependência projetivas e não-projetivas, evitando abordagens pseudo-projetivas. Para avaliar a sua eficácia, aplicamos o algoritmo Entropy Guided Transformation Learning aos corpora disponibilizados publicamente na tarefa proposta durante a CoNLL 2006. Esses experimentos foram realizados em três corpora de diferentes idiomas: dinamarquês, holandês e português. Para avaliação de desempenho foi utilizada a métrica de Unlabeled Attachment Score. Nossos resultados mostram que os modelos gerados atingem resultados acima da média dos sistemas do CoNLL. Ainda, nossos resultados indicam que a abordagem por classificação token-a-token é uma abordagem promissora para o problema de análise sintática de dependência.

[en] One of the most important tasks in Natural Language Processing is syntactic parsing, where the structure of a sentence is inferred according to a given grammar. Syntactic parsing, thus, tells us how to determine the meaning of the sentence fromthemeaning of the words in it. Syntactic parsing based on dependency grammars is called dependency parsing. The Dependency-based syntactic parsing task consists in identifying a head word for each word in an input sentence. Hence, its output is a rooted tree, where the nodes are the words in the sentence. This simple, yet powerful, structure is used in a great variety of applications, like Question Answering,Machine Translation, Information Extraction and Semantic Role Labeling. State-of-the-art dependency parsing systems use transition-based or graph-based models. This dissertation presents a token classification approach to dependency parsing, by creating a special tagging set that helps to correctly find the head of a token. Using this tagging style, any…

Advisors/Committee Members: RUY LUIZ MILIDIU.

Subjects/Keywords: [pt] APRENDIZAGEM; [en] LEARNING; [pt] PROCESSAMENTO DA LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING; [pt] CLASSIFICACAO TOKEN-A-TOKEN

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

CRESTANA, C. E. M. (2010). [en] A TOKEN CLASSIFICATION APPROACH TO DEPENDENCY PARSING. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16458

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

CRESTANA, CARLOS EDUARDO MEGER. “[en] A TOKEN CLASSIFICATION APPROACH TO DEPENDENCY PARSING.” 2010. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16458.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

CRESTANA, CARLOS EDUARDO MEGER. “[en] A TOKEN CLASSIFICATION APPROACH TO DEPENDENCY PARSING.” 2010. Web. 21 Jan 2021.

Vancouver:

CRESTANA CEM. [en] A TOKEN CLASSIFICATION APPROACH TO DEPENDENCY PARSING. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2010. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16458.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

CRESTANA CEM. [en] A TOKEN CLASSIFICATION APPROACH TO DEPENDENCY PARSING. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2010. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16458

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

6. ERALDO LUIS REZENDE FERNANDES. [en] ENTROPY GUIDED FEATURE GENERATION FOR STRUCTURE LEARNING.

Degree: 2014, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23812

►

[pt] Aprendizado de estruturas consiste em aprender um mapeamento de variáveis de entrada para saídas estruturadas a partir de exemplos de pares entrada-saída. Vários problemas… (more)

▼

[pt] Aprendizado de estruturas consiste em aprender um mapeamento de variáveis de entrada para saídas estruturadas a partir de exemplos de pares entrada-saída. Vários problemas importantes podem ser modelados desta maneira. O processamento de linguagem natural provê diversas tarefas que podem ser formuladas e solucionadas através do aprendizado de estruturas. Por exemplo, parsing de dependência envolve o reconhecimento de uma árvore implícita em uma frase. Geração de atributos é uma sub-tarefa importante do aprendizado de estruturas. Geralmente, esta sub-tarefa é realizada por um especialista que constrói gabaritos de atributos complexos e discriminativos através da combinação dos atributos básicos disponíveis na entrada. Esta é uma forma limitada e cara para geração de atributos e é reconhecida como um gargalo de modelagem. Neste trabalho, propomos um método automático para geração de atributos para problemas de aprendizado de estruturas. Este método é guiado por entropia já que é baseado na entropia condicional de variáveis locais de saída dados os atributos básicos. Comparamos experimentalmente o método proposto com dois métodos alternativos para geração de atributos: geração manual e métodos de kernel polinomial. Nossos resultados mostram que o método de geração de atributos guiado por entropia é superior aos dois métodos alternativos em diferentes aspectos. Nosso método é muito mais barato do que o método manual e computacionalmente mais rápido que o método baseado em kernel. Adicionalmente, ele permite o controle do seu poder de generalização mais facilmente do que métodos de kernel. Nós avaliamos nosso método em nove datasets envolvendo cinco tarefas de linguística computacional e quatro idiomas. Os sistemas desenvolvidos apresentam resultados comparáveis aos melhores sistemas atualmente e, particularmente para etiquetagem morfossintática, identificação de sintagmas, extração de citações e resolução de coreferência, obtêm os melhores resultados conhecidos para diferentes idiomas como Árabe, Chinês, Inglês e Português. Adicionalmente, nosso sistema de resolução de coreferência obteve o primeiro lugar na competição Conference on Computational Natural Language Learning 2012 Shared Task. O sistema vencedor foi determinado pela média de desempenho em três idiomas: Árabe, Chinês e Inglês. Nosso sistema obteve o melhor desempenho nos três idiomas avaliados. Nosso método de geração de atributos estende naturalmente o framework de aprendizado de estruturas e não está restrito a tarefas de processamento de linguagem natural.

[en] Structure learning consists in learning a mapping from inputs to structured outputs by means of a sample of correct input-output pairs. Many important problems fit into this setting. Natural language processing provides several tasks that can be formulated and solved as structure learning problems. Dependency parsing, for instance, involves the prediction of a tree underlying a sentence. Feature generation is an important subtask of structure learning which, usually, is partially solved by a…

Advisors/Committee Members: RUY LUIZ MILIDIU.

Subjects/Keywords: [pt] ENTROPIA; [en] ENTROPY; [pt] APRENDIZADO DE ESTRUTURAS; [pt] GERACAO DE ATRIBUTOS; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

FERNANDES, E. L. R. (2014). [en] ENTROPY GUIDED FEATURE GENERATION FOR STRUCTURE LEARNING. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23812

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

FERNANDES, ERALDO LUIS REZENDE. “[en] ENTROPY GUIDED FEATURE GENERATION FOR STRUCTURE LEARNING.” 2014. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23812.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

FERNANDES, ERALDO LUIS REZENDE. “[en] ENTROPY GUIDED FEATURE GENERATION FOR STRUCTURE LEARNING.” 2014. Web. 21 Jan 2021.

Vancouver:

FERNANDES ELR. [en] ENTROPY GUIDED FEATURE GENERATION FOR STRUCTURE LEARNING. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2014. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23812.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

FERNANDES ELR. [en] ENTROPY GUIDED FEATURE GENERATION FOR STRUCTURE LEARNING. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2014. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23812

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

7. Konstas, Ioannis. Joint models for concept-to-text generation.

Degree: PhD, 2014, University of Edinburgh

URL: http://hdl.handle.net/1842/8926

► Much of the data found on the world wide web is in numeric, tabular, or other nontextual format (e.g., weather forecast tables, stock market charts,… (more)

▼ Much of the data found on the world wide web is in numeric, tabular, or other nontextual format (e.g., weather forecast tables, stock market charts, live sensor feeds), and thus inaccessible to non-experts or laypersons. However, most conventional search engines and natural language processing tools (e.g., summarisers) can only handle textual input. As a result, data in non-textual form remains largely inaccessible. Concept-to-text generation refers to the task of automatically producing textual output from non-linguistic input, and holds promise for rendering non-linguistic data widely accessible. Several successful generation systems have been produced in the past twenty years. They mostly rely on human-crafted rules or expert-driven grammars, implement a pipeline architecture, and usually operate in a single domain. In this thesis, we present several novel statistical models that take as input a set of database records and generate a description of them in natural language text. Our unique idea is to combine the processes of structuring a document (document planning), deciding what to say (content selection) and choosing the specific words and syntactic constructs specifying how to say it (lexicalisation and surface realisation), in a uniform joint manner. Rather than breaking up the generation process into a sequence of local decisions, we define a probabilistic context-free grammar that globally describes the inherent structure of the input (a corpus of database records and text describing some of them). This joint representation allows individual processes (i.e., document planning, content selection, and surface realisation) to communicate and influence each other naturally. We recast generation as the task of finding the best derivation tree for a set of input database records and our grammar, and describe several algorithms for decoding in this framework that allows to intersect the grammar with additional information capturing fluency and syntactic well-formedness constraints. We implement our generators using the hypergraph framework. Contrary to traditional systems, we learn all the necessary document, structural and linguistic knowledge from unannotated data. Additionally, we explore a discriminative reranking approach on the hypergraph representation of our model, by including more refined content selection features. Central to our approach is the idea of porting our models to various domains; we experimented on four widely different domains, namely sportscasting, weather forecast generation, booking flights, and troubleshooting guides. The performance of our systems is competitive and often superior compared to state-of-the-art systems that use domain specific constraints, explicit feature engineering or labelled data.

Subjects/Keywords: 006.3; natural language generation; natural language processing

10 more images…

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Konstas, I. (2014). Joint models for concept-to-text generation. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/8926

Chicago Manual of Style (16^th Edition):

Konstas, Ioannis. “Joint models for concept-to-text generation.” 2014. Doctoral Dissertation, University of Edinburgh. Accessed January 21, 2021. http://hdl.handle.net/1842/8926.

MLA Handbook (7^th Edition):

Konstas, Ioannis. “Joint models for concept-to-text generation.” 2014. Web. 21 Jan 2021.

Vancouver:

Konstas I. Joint models for concept-to-text generation. [Internet] [Doctoral dissertation]. University of Edinburgh; 2014. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1842/8926.

Council of Science Editors:

Konstas I. Joint models for concept-to-text generation. [Doctoral Dissertation]. University of Edinburgh; 2014. Available from: http://hdl.handle.net/1842/8926

Delft University of Technology

8. Wang, Zina (author). Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:2a448e6d-e1e8-4b01-a97e-dcf2e9074560

► Relation extraction has been considered as one of the most popular topics nowadays, thanks for its common application in knowledge graph, machine reading and other… (more)

Subjects/Keywords: Natural Language Understanding; Natural Language Processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wang, Z. (. (2020). Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2a448e6d-e1e8-4b01-a97e-dcf2e9074560

Chicago Manual of Style (16^th Edition):

Wang, Zina (author). “Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language.” 2020. Masters Thesis, Delft University of Technology. Accessed January 21, 2021. http://resolver.tudelft.nl/uuid:2a448e6d-e1e8-4b01-a97e-dcf2e9074560.

MLA Handbook (7^th Edition):

Wang, Zina (author). “Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language.” 2020. Web. 21 Jan 2021.

Vancouver:

Wang Z(. Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Jan 21]. Available from: http://resolver.tudelft.nl/uuid:2a448e6d-e1e8-4b01-a97e-dcf2e9074560.

Council of Science Editors:

Wang Z(. Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:2a448e6d-e1e8-4b01-a97e-dcf2e9074560

Ryerson University

9. Krezolek, Michal Andrzej. Natural Language Learning.

Degree: 2010, Ryerson University

URL: https://digital.library.ryerson.ca/islandora/object/RULA%3A635

► This thesis is a small step towards automated learning of natural languages. With the use of a parser that incorporates machine-learning algorithms, our algorithm is… (more)

Subjects/Keywords: Natural language processing; Machine learning

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Krezolek, M. A. (2010). Natural Language Learning. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A635

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Krezolek, Michal Andrzej. “Natural Language Learning.” 2010. Thesis, Ryerson University. Accessed January 21, 2021. https://digital.library.ryerson.ca/islandora/object/RULA%3A635.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Krezolek, Michal Andrzej. “Natural Language Learning.” 2010. Web. 21 Jan 2021.

Vancouver:

Krezolek MA. Natural Language Learning. [Internet] [Thesis]. Ryerson University; 2010. [cited 2021 Jan 21]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A635.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Krezolek MA. Natural Language Learning. [Thesis]. Ryerson University; 2010. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A635

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

10. Irvine, Ann. Using Comparable Corpora to Augment Statistical Machine Translation Models in Low Resource Settings.

Degree: 2014, Johns Hopkins University

URL: http://jhir.library.jhu.edu/handle/1774.2/38018

► Previously, statistical machine translation (SMT) models have been estimated from parallel corpora, or pairs of translated sentences. In this thesis, we directly incorporate comparable corpora… (more)

▼ Previously, statistical machine translation (SMT) models have been estimated from parallel corpora, or pairs of translated sentences. In this thesis, we directly incorporate comparable corpora into the estimation of end-to-end SMT models. In contrast to parallel corpora, comparable corpora are pairs of monolingual corpora that have some cross-lingual similarities, for example topic or publication date, but that do not necessarily contain any direct translations. Comparable corpora are more readily available in large quantities than parallel corpora, which require significant human effort to compile. We use comparable corpora to estimate machine translation model parameters and show that doing so improves performance in settings where a limited amount of parallel data is available for training. The major contributions of this thesis are the following: * We release ‘language packs’ for 151 human languages, which include bilingual dictionaries, comparable corpora of Wikipedia document pairs, comparable corpora of time-stamped news text that we harvested from the web, and, for non-roman script languages, dictionaries of name pairs, which are likely to be transliterations. * We present a novel technique for using a small number of example word translations to learn a supervised model for bilingual lexicon induction which takes advantage of a wide variety of signals of translation equivalence that can be estimated over comparable corpora. * We show that using comparable corpora to induce new translations and estimate new phrase table feature functions improves end-to-end statistical machine translation performance for low resource language pairs as well as domains. * We present a novel algorithm for composing multiword phrase translations from multiple unigram translations and then use comparable corpora to prune the large space of hypothesis translations. We show that these induced phrase translations improve machine translation performance beyond that of component unigrams. This thesis focuses on critical low resource machine translation settings, where insufficient parallel corpora exist for training statistical models. We experiment with both low resource language pairs and low resource domains of text. We present results from our novel error analysis methodology, which show that most translation errors in low resource settings are due to unseen source language words and phrases and unseen target language translations. We also find room for fixing errors due to how different translations are weighted, or scored, in the models. We target both error types; we use comparable corpora to induce new word and phrase translations and estimate novel translation feature scores. Our experiments show that augmenting baseline SMT systems with new translations and features estimated over comparable corpora improves translation performance significantly. Additionally, our techniques expand the applicability of statistical machine translation to those language pairs for which zero parallel text is available. Advisors/Committee Members: Callison-Burch, Chris (advisor).

Subjects/Keywords: machine translation; natural language processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Irvine, A. (2014). Using Comparable Corpora to Augment Statistical Machine Translation Models in Low Resource Settings. (Thesis). Johns Hopkins University. Retrieved from http://jhir.library.jhu.edu/handle/1774.2/38018

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Irvine, Ann. “Using Comparable Corpora to Augment Statistical Machine Translation Models in Low Resource Settings.” 2014. Thesis, Johns Hopkins University. Accessed January 21, 2021. http://jhir.library.jhu.edu/handle/1774.2/38018.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Irvine, Ann. “Using Comparable Corpora to Augment Statistical Machine Translation Models in Low Resource Settings.” 2014. Web. 21 Jan 2021.

Vancouver:

Irvine A. Using Comparable Corpora to Augment Statistical Machine Translation Models in Low Resource Settings. [Internet] [Thesis]. Johns Hopkins University; 2014. [cited 2021 Jan 21]. Available from: http://jhir.library.jhu.edu/handle/1774.2/38018.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Irvine A. Using Comparable Corpora to Augment Statistical Machine Translation Models in Low Resource Settings. [Thesis]. Johns Hopkins University; 2014. Available from: http://jhir.library.jhu.edu/handle/1774.2/38018

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Georgia

11. Tarkhadkar, Sagar Santosh. Mutaimpact miner.

Degree: 2014, University of Georgia

URL: http://hdl.handle.net/10724/30031

► Manual curation of knowledge from biomedical literature is both expensive and time consuming. Scientific publications in biomedicine have an enormous amount of valuable information on… (more)

Subjects/Keywords: text mining; Natural Language Processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Tarkhadkar, S. S. (2014). Mutaimpact miner. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/30031

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tarkhadkar, Sagar Santosh. “Mutaimpact miner.” 2014. Thesis, University of Georgia. Accessed January 21, 2021. http://hdl.handle.net/10724/30031.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tarkhadkar, Sagar Santosh. “Mutaimpact miner.” 2014. Web. 21 Jan 2021.

Vancouver:

Tarkhadkar SS. Mutaimpact miner. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10724/30031.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tarkhadkar SS. Mutaimpact miner. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/30031

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Vanderbilt University

12. Davis, Mary Feller. Determining the Use of Electronic Medical Records in Genetic Studies of Multiple Sclerosis.

Degree: PhD, Human Genetics, 2013, Vanderbilt University

URL: http://hdl.handle.net/1803/14936

► The clinical course of multiple sclerosis (MS) is highly variable, and research data collection is costly and time-consuming. Much is known about the genetic risk… (more)

Subjects/Keywords: genetic association; natural language processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Davis, M. F. (2013). Determining the Use of Electronic Medical Records in Genetic Studies of Multiple Sclerosis. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14936

Chicago Manual of Style (16^th Edition):

Davis, Mary Feller. “Determining the Use of Electronic Medical Records in Genetic Studies of Multiple Sclerosis.” 2013. Doctoral Dissertation, Vanderbilt University. Accessed January 21, 2021. http://hdl.handle.net/1803/14936.

MLA Handbook (7^th Edition):

Davis, Mary Feller. “Determining the Use of Electronic Medical Records in Genetic Studies of Multiple Sclerosis.” 2013. Web. 21 Jan 2021.

Vancouver:

Davis MF. Determining the Use of Electronic Medical Records in Genetic Studies of Multiple Sclerosis. [Internet] [Doctoral dissertation]. Vanderbilt University; 2013. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1803/14936.

Council of Science Editors:

Davis MF. Determining the Use of Electronic Medical Records in Genetic Studies of Multiple Sclerosis. [Doctoral Dissertation]. Vanderbilt University; 2013. Available from: http://hdl.handle.net/1803/14936

13. Choe, Do Kook. Toward Solving Penn Treebank Parsing.

Degree: Department of Computer Science, 2017, Brown University

URL: https://repository.library.brown.edu/studio/item/bdr:733298/

► A natural language parser recovers the latent grammatical structures of sentences. In many natural language processing (NLP) applications, parsing is applied to sentences first and… (more)

Subjects/Keywords: Natural language processing (Computer science)

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Choe, D. K. (2017). Toward Solving Penn Treebank Parsing. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733298/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Choe, Do Kook. “Toward Solving Penn Treebank Parsing.” 2017. Thesis, Brown University. Accessed January 21, 2021. https://repository.library.brown.edu/studio/item/bdr:733298/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Choe, Do Kook. “Toward Solving Penn Treebank Parsing.” 2017. Web. 21 Jan 2021.

Vancouver:

Choe DK. Toward Solving Penn Treebank Parsing. [Internet] [Thesis]. Brown University; 2017. [cited 2021 Jan 21]. Available from: https://repository.library.brown.edu/studio/item/bdr:733298/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Choe DK. Toward Solving Penn Treebank Parsing. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733298/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Arizona

14. Luri Rodriguez, Ignacio. Listening to the Market: Text Analysis Approaches to Consumer Research .

Degree: 2020, University of Arizona

URL: http://hdl.handle.net/10150/641701

► Language is central to human interaction, thinking, and sense-making. Witty marketing communicators and loquacious consumer research scholars can bend and shape language to great effect… (more)

▼ Language is central to human interaction, thinking, and sense-making. Witty marketing communicators and loquacious consumer research scholars can bend and shape language to great effect and be admired for it. Marketing has traditionally been a diverse discipline, borrowing from many parents and employing a variety of methods or approaches to understanding consumers and the market. This dissertation presents three essays exploring consumer behavior from a perspective influenced by theory and methods from language- and discourse-centric disciplines. The first essay employs ethnographic methods informed by discourse analysis of marketing communications and in-person service encounters to better understand services. We integrate the disconnected research streams of role theory in service encounters and cocreation. Our findings challenge common definitions of a service script, defining instead as the product of imagined service encounters that serve as a template for cocreation in consumers’ minds. The second essay examines U.S. news media on the topic of debt in order to reveal how public discourse frames debt to distribute responsibility and guide action. The data analysis begins at the qualitative level of discourse analysis and hermeneutics, followed by a corpus research approach, complemented with a neural network-based word embedding technique used in Natural Language Processing (NLP). Our findings reveal two dominant metaphors in public debt conversations: debt as weight, and debt as captivity. These metaphors frame the discourse, creating narratives with contrasting assignments of responsibility in the market and proposed marketing actions. The third essay utilizes the same U.S. news articles database of the second paper to answer different research questions. We join a growing and incredibly impactful new stream of consumer research studies harnessing the power of big textual data for marketing insight. We make a methodological contribution by developing and training a topic-detection Bi-directional long short term memory (Bi-LSTM) neural network to classify a large, unstructured corpus. We sequentially ran a dynamic Latent Dietrich Allocation (LDA) to identify the narratives predominant to each type of debt and how they change over the ten-year period (2010-2019). Advisors/Committee Members: Schau, Hope J (advisor), Ghosh, Bikram (committeemember), Taillard, Marie (committeemember), Sias, Rick (committeemember).

Subjects/Keywords: discourse; marketing; natural language processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Luri Rodriguez, I. (2020). Listening to the Market: Text Analysis Approaches to Consumer Research . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/641701

Chicago Manual of Style (16^th Edition):

Luri Rodriguez, Ignacio. “Listening to the Market: Text Analysis Approaches to Consumer Research .” 2020. Doctoral Dissertation, University of Arizona. Accessed January 21, 2021. http://hdl.handle.net/10150/641701.

MLA Handbook (7^th Edition):

Luri Rodriguez, Ignacio. “Listening to the Market: Text Analysis Approaches to Consumer Research .” 2020. Web. 21 Jan 2021.

Vancouver:

Luri Rodriguez I. Listening to the Market: Text Analysis Approaches to Consumer Research . [Internet] [Doctoral dissertation]. University of Arizona; 2020. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10150/641701.

Council of Science Editors:

Luri Rodriguez I. Listening to the Market: Text Analysis Approaches to Consumer Research . [Doctoral Dissertation]. University of Arizona; 2020. Available from: http://hdl.handle.net/10150/641701

University of Guelph

15. Stantic, Daniel. A Unified Probabilistic Model for Aspect-Level Sentiment Analysis.

Degree: MS, School of Computer Science, 2016, University of Guelph

URL: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616

► In this thesis, we develop a new probabilistic model for aspect-level sentiment analysis based on POSLDA, a topic classifier that incorporates syntax modelling for better… (more)

Subjects/Keywords: natural language processing; sentiment analysis

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Stantic, D. (2016). A Unified Probabilistic Model for Aspect-Level Sentiment Analysis. (Masters Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616

Chicago Manual of Style (16^th Edition):

Stantic, Daniel. “A Unified Probabilistic Model for Aspect-Level Sentiment Analysis.” 2016. Masters Thesis, University of Guelph. Accessed January 21, 2021. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616.

MLA Handbook (7^th Edition):

Stantic, Daniel. “A Unified Probabilistic Model for Aspect-Level Sentiment Analysis.” 2016. Web. 21 Jan 2021.

Vancouver:

Stantic D. A Unified Probabilistic Model for Aspect-Level Sentiment Analysis. [Internet] [Masters thesis]. University of Guelph; 2016. [cited 2021 Jan 21]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616.

Council of Science Editors:

Stantic D. A Unified Probabilistic Model for Aspect-Level Sentiment Analysis. [Masters Thesis]. University of Guelph; 2016. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9616

University of Houston

16. Kulkarni, Akshay Bhavani Kumar 1994-. Early Detection of Depression.

Degree: MS, Computer Science, 2018, University of Houston

URL: http://hdl.handle.net/10657/3089

► Depression is a mental disorder that affects more than 300 million people worldwide. An individual suffering from depression functions poorly in life, is prone to… (more)

▼ Depression is a mental disorder that affects more than 300 million people worldwide. An individual suffering from depression functions poorly in life, is prone to other diseases and in the worst-case, depression leads to suicide. There are many impediments that prevent expert care from reaching people suffering from depression in time. Impediments such as social stigma associated with mental disorders, lack of trained health-care professionals and ignorance of the signs of depression owing to a lack of awareness of the disease. Moreover, the World Health Organization (WHO) claims that individuals who are depressed are often not correctly diagnosed and others who are misdiagnosed are prescribed antidepressants. Thus, there is a strong need to automatically assess the risk of depression. Identification of depression from social media has been framed as a classification problem in the field of Natural Language Processing (NLP). In this work we study NLP approaches that can successfully extract information from textual data to enhance identification of depression. These NLP approaches perform feature extraction to build document representations. The issues of detecting depression in a social media environment is data scarcity for users with depression and the inherent noise associated with social media data. We attempt to address those issues by using representations that can naturally cope with a social media environment. Specifically, we propose the usage of Distributed Term Representations (DTRs) to capture information that can be used by supervised machine learning methods for learning and classifying users suffering from depression. Experimental evaluation provides evidence that DTRs are more effective for depression detection than traditional representations such as Bag of Words (BOW) and representations based on neural word embeddings. In fact, we have obtained state-of-the-art results with Document Occurrence Representation (DOR) for depression detection (F1-Score 0.66 on the depressed class). For early detection of depression, we have obtained the lowest reported Early Risk Detection Error (ERDE) using Pyramidal a newly adapted method that is used for computing document representations. Advisors/Committee Members: Solorio, Thamar (advisor), Gonzalez, Fabio A. (committee member), Eick, Christoph F. (committee member).

Subjects/Keywords: Natural Language Processing; Health care

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kulkarni, A. B. K. 1. (2018). Early Detection of Depression. (Masters Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3089

Chicago Manual of Style (16^th Edition):

Kulkarni, Akshay Bhavani Kumar 1994-. “Early Detection of Depression.” 2018. Masters Thesis, University of Houston. Accessed January 21, 2021. http://hdl.handle.net/10657/3089.

MLA Handbook (7^th Edition):

Kulkarni, Akshay Bhavani Kumar 1994-. “Early Detection of Depression.” 2018. Web. 21 Jan 2021.

Vancouver:

Kulkarni ABK1. Early Detection of Depression. [Internet] [Masters thesis]. University of Houston; 2018. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10657/3089.

Council of Science Editors:

Kulkarni ABK1. Early Detection of Depression. [Masters Thesis]. University of Houston; 2018. Available from: http://hdl.handle.net/10657/3089

University of Victoria

17. Sedghi, Elham. A novel stroke prediction model based on clinical natural language processing (NLP) and data mining methods.

Degree: Department of Computer Science, 2017, University of Victoria

URL: http://hdl.handle.net/1828/7879

► Early detection and treatment of stroke can save lives. Before any procedure is planned, the patient is traditionally subjected to a brain scan such as… (more)

▼ Early detection and treatment of stroke can save lives. Before any procedure is planned, the patient is traditionally subjected to a brain scan such as Magnetic Resonance Imaging (MRI) in order to make sure he/she receives a safe treatment. Before any imaging is performed, the patient is checked into Emergency Room (ER) and clinicians from the Stroke Rapid Assessment Unit (SRAU) perform an evaluation of the patient's signs and symptoms. The question we address in this thesis is: Can Data Mining (DM) algorithms be employed to reliably predict the occurrence of stroke in a patient based on the signs and symptoms gathered by the clinicians and other staff in the ER or the SRAU? A reliable DM algorithm would be very useful in helping the clinicians make a better decision whether to escalate the case or classify it as a non-life threatening mimic and not put the patient through unnecessary imaging and tests. Such an algorithm would not only make the life of patients and clinicians easier but would also enable the hospitals to cut down on their costs. Most of the signs and symptoms gathered by clinicians in the ER or the SRAU are stored in free-text format in hospital information systems. Using techniques from Natural Language Processing (NLP), the vocabularies of interest can be extracted and classiffied. A big challenge in this process is that medical narratives are full of misspelled words and clinical abbreviations. It is a well known fact that the quality of data mining results crucially depends on the quality of input data. In this thesis, as a rst contribution, we describe a procedure to preprocess the raw data and transform it into clean, well-structured data that can be effectively used by DM learning algorithms. Another contribution of this thesis is producing a set of carefully crafted rules to perform detection of negated meaning in free-text sentences. Using these rules, we were able to get the correct semantics of sentences and provide much more useful datasets to DM learning algorithms. This thesis consists of three main parts. In the first part, we focus on building classi ers to reliably distinguish stroke and Transient Ischemic Attack (TIA) from mimic cases. For this, we used text extracted from the "chief complaint" and "history of patient illness" fields available in the patients' les at the Victoria General Hospital (VGH). In collaboration with stroke specialists, we identified a well-de ned set of stroke-related keywords. Next, we created practical tools to accurately assign keywords from this set to each patient. Then, we performed extensive experiments for nding the right learning algorithm to build the best classifier that provides a good balance between sensitivity, specificity, and a host of other quality indicators. In the second part, we focus on the most important mimic case, migraine, and how to e ectively distinguish it from stroke or TIA. This is a challenging problem because migraine has many signs and symptoms that are similar to those of stroke or TIA. Another challenge we address is… Advisors/Committee Members: Thomo, Alex (supervisor), Weber, Jens H. (supervisor).

Subjects/Keywords: Data Mining; Natural Language Processing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sedghi, E. (2017). A novel stroke prediction model based on clinical natural language processing (NLP) and data mining methods. (Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/7879

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sedghi, Elham. “A novel stroke prediction model based on clinical natural language processing (NLP) and data mining methods.” 2017. Thesis, University of Victoria. Accessed January 21, 2021. http://hdl.handle.net/1828/7879.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sedghi, Elham. “A novel stroke prediction model based on clinical natural language processing (NLP) and data mining methods.” 2017. Web. 21 Jan 2021.

Vancouver:

Sedghi E. A novel stroke prediction model based on clinical natural language processing (NLP) and data mining methods. [Internet] [Thesis]. University of Victoria; 2017. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/1828/7879.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sedghi E. A novel stroke prediction model based on clinical natural language processing (NLP) and data mining methods. [Thesis]. University of Victoria; 2017. Available from: http://hdl.handle.net/1828/7879

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Minnesota

18. Exley, Andrew. Improvements to a Speech Repair Parser.

Degree: PhD, Computer Science, 2016, University of Minnesota

URL: http://hdl.handle.net/11299/181724

► Parsing is a common task for speech-recognition systems, but many parsers ignore the possibility of speech errors and repairs, which are very common in conversational… (more)

Subjects/Keywords: Natural Language Processing; Parsing

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Exley, A. (2016). Improvements to a Speech Repair Parser. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/181724

Chicago Manual of Style (16^th Edition):

Exley, Andrew. “Improvements to a Speech Repair Parser.” 2016. Doctoral Dissertation, University of Minnesota. Accessed January 21, 2021. http://hdl.handle.net/11299/181724.

MLA Handbook (7^th Edition):

Exley, Andrew. “Improvements to a Speech Repair Parser.” 2016. Web. 21 Jan 2021.

Vancouver:

Exley A. Improvements to a Speech Repair Parser. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/11299/181724.

Council of Science Editors:

Exley A. Improvements to a Speech Repair Parser. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/181724

Virginia Tech

19. Patil, Supritha Basavaraj. Analysis of Moving Events Using Tweets.

Degree: MS, Computer Science and Applications, 2019, Virginia Tech

URL: http://hdl.handle.net/10919/90884

► News now travels faster on social media than through news channels. Information from social media can help retrieve minute details that might not be emphasized… (more)

Subjects/Keywords: Natural Language Processing; Twitter

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Patil, S. B. (2019). Analysis of Moving Events Using Tweets. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/90884

Chicago Manual of Style (16^th Edition):

Patil, Supritha Basavaraj. “Analysis of Moving Events Using Tweets.” 2019. Masters Thesis, Virginia Tech. Accessed January 21, 2021. http://hdl.handle.net/10919/90884.

MLA Handbook (7^th Edition):

Patil, Supritha Basavaraj. “Analysis of Moving Events Using Tweets.” 2019. Web. 21 Jan 2021.

Vancouver:

Patil SB. Analysis of Moving Events Using Tweets. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10919/90884.

Council of Science Editors:

Patil SB. Analysis of Moving Events Using Tweets. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/90884

Virginia Tech

20. Kakusa, Takondwa Lisungu. Use of Assembly Inspired Instructions in the Allowance of Natural Language Processing in ROS.

Degree: MS, Computer Engineering, 2018, Virginia Tech

URL: http://hdl.handle.net/10919/84521

► Natural Language processing is a growing field and widely used in both industrial and and commercial cases. Though it is difficult to create a natural… (more)

Subjects/Keywords: Natural Language Processing; Robotics; ROS

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kakusa, T. L. (2018). Use of Assembly Inspired Instructions in the Allowance of Natural Language Processing in ROS. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84521

Chicago Manual of Style (16^th Edition):

Kakusa, Takondwa Lisungu. “Use of Assembly Inspired Instructions in the Allowance of Natural Language Processing in ROS.” 2018. Masters Thesis, Virginia Tech. Accessed January 21, 2021. http://hdl.handle.net/10919/84521.

MLA Handbook (7^th Edition):

Kakusa, Takondwa Lisungu. “Use of Assembly Inspired Instructions in the Allowance of Natural Language Processing in ROS.” 2018. Web. 21 Jan 2021.

Vancouver:

Kakusa TL. Use of Assembly Inspired Instructions in the Allowance of Natural Language Processing in ROS. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/10919/84521.

Council of Science Editors:

Kakusa TL. Use of Assembly Inspired Instructions in the Allowance of Natural Language Processing in ROS. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/84521

University of Sydney

21. Pink, Glen Alan. Slot Filling .

Degree: 2017, University of Sydney

URL: http://hdl.handle.net/2123/17055

► Slot filling (SF) is the task of automatically extracting facts about particular entities from unstructured text, and populating a knowledge base (KB) with these facts.… (more)

▼ Slot filling (SF) is the task of automatically extracting facts about particular entities from unstructured text, and populating a knowledge base (KB) with these facts. These structured KBs enable applications such as structured web queries and question answering. SF is typically framed as a query-oriented setting of the related task of relation extraction. Throughout this thesis, we reflect on how SF is a task with many distinct problems. We demonstrate that recall is a major limiter on SF system performance. We contribute an analysis of typical SF recall loss, and find a substantial amount of loss occurs early in the SF pipeline. We confirm that accurate NER and coreference resolution are required for high-recall SF. We measure upper bounds using a naïve graph-based semi-supervised bootstrapping technique, and find that only 39% of results are reachable using a typical feature space. We expect that this graph-based technique will be directly useful for extraction, and this leads us to frame SF as a label propagation task. We focus on a detailed graph representation of the task which reflects the behaviour and assumptions we want to model based on our analysis, including modifying the label propagation process to model multiple types of label interaction. Analysing the graph, we find that a large number of errors occur in very close proximity to training data, and identify that this is of major concern for propagation. While there are some conflicts caused by a lack of sufficient disambiguating context—we explore adding additional contextual features to address this—many of these conflicts are caused by subtle annotation problems. We find that lack of a standard for how explicit expressions of relations must be in text makes consistent annotation difficult. Using a strict definition of explicitness results in 20% of correct annotations being removed from a standard dataset. We contribute several annotation-driven analyses of this problem, exploring the definition of slots and the effect of the lack of a concrete definition of explicitness: annotation schema do not detail how explicit expressions of relations need to be, and there is large scope for disagreement between annotators. Additionally, applications may require relatively strict or relaxed evidence for extractions, but this is not considered in annotation tasks. We demonstrate that annotators frequently disagree on instances, dependent on differences in annotator world knowledge and thresholds on making probabilistic inference. SF is fundamental to enabling many knowledge-based applications, and this work motivates modelling and evaluating SF to better target these tasks.

Subjects/Keywords: natural language processing; information; extraction

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Pink, G. A. (2017). Slot Filling . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/17055

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Pink, Glen Alan. “Slot Filling .” 2017. Thesis, University of Sydney. Accessed January 21, 2021. http://hdl.handle.net/2123/17055.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Pink, Glen Alan. “Slot Filling .” 2017. Web. 21 Jan 2021.

Vancouver:

Pink GA. Slot Filling . [Internet] [Thesis]. University of Sydney; 2017. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/2123/17055.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pink GA. Slot Filling . [Thesis]. University of Sydney; 2017. Available from: http://hdl.handle.net/2123/17055

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Texas – Austin

22. -7062-2970. Advances in statistical script learning.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/63480

► When humans encode information into natural language, they do so with the clear assumption that the reader will be able to seamlessly make inferences based… (more)

▼ When humans encode information into natural language, they do so with the clear assumption that the reader will be able to seamlessly make inferences based on world knowledge. For example, given the sentence ``Mrs. Dalloway said she would buy the flowers herself,'' one can make a number of probable inferences based on event co-occurrences: she bought flowers, she went to a store, she took the flowers home, and so on. Observing this, it is clear that many different useful natural language end-tasks could benefit from models of events as they typically co-occur (so-called script models). Robust question-answering systems must be able to infer highly-probable implicit events from what is explicitly stated in a text, as must robust information-extraction systems that map from unstructured text to formal assertions about relations expressed in the text. Coreference resolution systems, semantic role labeling, and even syntactic parsing systems could, in principle, benefit from event co-occurrence models. To this end, we present a number of contributions related to statistical event co-occurrence models. First, we investigate a method of incorporating multiple entities into events in a count-based co-occurrence model. We find that modeling multiple entities interacting across events allows for improved empirical performance on the task of modeling sequences of events in documents. Second, we give a method of applying Recurrent Neural Network sequence models to the task of predicting held-out predicate-argument structures from documents. This model allows us to easily incorporate entity noun information, and can allow for more complex, higher-arity events than a count-based co-occurrence model. We find the neural model improves performance considerably over the count-based co-occurrence model. Third, we investigate the performance of a sequence-to-sequence encoder-decoder neural model on the task of predicting held-out predicate-argument events from text. This model does not explicitly model any external syntactic information, and does not require a parser. We find the text-level model to be competitive in predictive performance with an event level model directly mediated by an external syntactic analysis. Finally, motivated by this result, we investigate incorporating features derived from these models into a baseline noun coreference resolution system. We find that, while our additional features do not appreciably improve top-level performance, we can nonetheless provide empirical improvement on a number of restricted classes of difficult coreference decisions. Advisors/Committee Members: Mooney, Raymond J. (Raymond Joseph) (advisor), Chambers, Nathanael (committee member), Erk, Katrin (committee member), Stone, Peter (committee member).

Subjects/Keywords: Natural language processing; Machine learning

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

-7062-2970. (2017). Advances in statistical script learning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63480

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-7062-2970. “Advances in statistical script learning.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed January 21, 2021. http://hdl.handle.net/2152/63480.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-7062-2970. “Advances in statistical script learning.” 2017. Web. 21 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7062-2970. Advances in statistical script learning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/2152/63480.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7062-2970. Advances in statistical script learning. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/63480

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

University of Texas – Austin

23. Tausczik, Yla Rebecca. Changing group dynamics through computerized language feedback.

Degree: PhD, Psychology, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2012-08-5971

► Why do some groups of people work well together while others do not? It is commonly accepted that effective groups communicate well. Yet one of… (more)

Subjects/Keywords: Teamwork; Natural language processing; Intervention

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Tausczik, Y. R. (2012). Changing group dynamics through computerized language feedback. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-08-5971

Chicago Manual of Style (16^th Edition):

Tausczik, Yla Rebecca. “Changing group dynamics through computerized language feedback.” 2012. Doctoral Dissertation, University of Texas – Austin. Accessed January 21, 2021. http://hdl.handle.net/2152/ETD-UT-2012-08-5971.

MLA Handbook (7^th Edition):

Tausczik, Yla Rebecca. “Changing group dynamics through computerized language feedback.” 2012. Web. 21 Jan 2021.

Vancouver:

Tausczik YR. Changing group dynamics through computerized language feedback. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5971.

Council of Science Editors:

Tausczik YR. Changing group dynamics through computerized language feedback. [Doctoral Dissertation]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5971

Pontifical Catholic University of Rio de Janeiro

24. SILVANO NOGUEIRA BUBACK. [en] USING MACHINE LEARNING TO BUILD A TOOL THAT HELPS COMMENTS MODERATION.

Degree: 2012, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19232

►

[pt] Uma das mudanças trazidas pela Web 2.0 é a maior participação dos usuários na produção do conteúdo, através de opiniões em redes sociais ou… (more)

▼

[pt] Uma das mudanças trazidas pela Web 2.0 é a maior participação dos usuários na produção do conteúdo, através de opiniões em redes sociais ou comentários nos próprios sites de produtos e serviços. Estes comentários são muito valiosos para seus sites pois fornecem feedback e incentivam a participação e divulgação do conteúdo. Porém excessos podem ocorrer através de comentários com palavrões indesejados ou spam. Enquanto para alguns sites a própria moderação da comunidade é suficiente, para outros as mensagens indesejadas podem comprometer o serviço. Para auxiliar na moderação dos comentários foi construída uma ferramenta que utiliza técnicas de aprendizado de máquina para auxiliar o moderador. Para testar os resultados, dois corpora de comentários produzidos na Globo.com foram utilizados, o primeiro com 657.405 comentários postados diretamente no site, e outro com 451.209 mensagens capturadas do Twitter. Nossos experimentos mostraram que o melhor resultado é obtido quando se separa o aprendizado dos comentários de acordo com o tema sobre o qual está sendo comentado.

[en] One of the main changes brought by Web 2.0 is the increase of user participation in content generation mainly in social networks and comments in news and service sites. These comments are valuable to the sites because they bring feedback and motivate other people to participate and to spread the content. On the other hand these comments also bring some kind of abuse as bad words and spam. While for some sites their own community moderation is enough, for others this impropriate content may compromise its content. In order to help theses sites, a tool that uses machine learning techniques was built to mediate comments. As a test to compare results, two datasets captured from Globo.com were used: the first one with 657.405 comments posted through its site and the second with 451.209 messages captured from Twitter. Our experiments show that best result is achieved when comment learning is done according to the subject that is being commented.

Advisors/Committee Members: MARCO ANTONIO CASANOVA, MARCO ANTONIO CASANOVA, MARCO ANTONIO CASANOVA.

Subjects/Keywords: [pt] CLASSIFICACAO DE TEXTOS; [en] TEXT CLASSIFICATION; [pt] PROCESSAMENTO DA LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING; [pt] SVM; [en] SVM; [pt] BOOSTING; [en] BOOSTING

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

BUBACK, S. N. (2012). [en] USING MACHINE LEARNING TO BUILD A TOOL THAT HELPS COMMENTS MODERATION. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19232

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

BUBACK, SILVANO NOGUEIRA. “[en] USING MACHINE LEARNING TO BUILD A TOOL THAT HELPS COMMENTS MODERATION.” 2012. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19232.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

BUBACK, SILVANO NOGUEIRA. “[en] USING MACHINE LEARNING TO BUILD A TOOL THAT HELPS COMMENTS MODERATION.” 2012. Web. 21 Jan 2021.

Vancouver:

BUBACK SN. [en] USING MACHINE LEARNING TO BUILD A TOOL THAT HELPS COMMENTS MODERATION. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2012. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19232.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

BUBACK SN. [en] USING MACHINE LEARNING TO BUILD A TOOL THAT HELPS COMMENTS MODERATION. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2012. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19232

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

25. LUCIANA ROSA REDLICH. [en] TRAFFIC EVENTS MODELING BASED ON CLIPPING OF HUGE QUANTITY OF DATA FROM THE WEB.

Degree: 2015, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23940

►

[pt] Este trabalho consiste no desenvolvimento de um modelo que auxilie na análise de eventos ocorridos no trânsito das grandes cidades. Utilizando uma grande massa… (more)

Subjects/Keywords: [pt] APRENDIZADO DE MAQUINA; [en] MACHINE LEARNING; [pt] ONTOLOGIAS; [en] ONTOLOGIES; [pt] EVENTO; [en] EVENT; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

REDLICH, L. R. (2015). [en] TRAFFIC EVENTS MODELING BASED ON CLIPPING OF HUGE QUANTITY OF DATA FROM THE WEB. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23940

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

REDLICH, LUCIANA ROSA. “[en] TRAFFIC EVENTS MODELING BASED ON CLIPPING OF HUGE QUANTITY OF DATA FROM THE WEB.” 2015. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23940.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

REDLICH, LUCIANA ROSA. “[en] TRAFFIC EVENTS MODELING BASED ON CLIPPING OF HUGE QUANTITY OF DATA FROM THE WEB.” 2015. Web. 21 Jan 2021.

Vancouver:

REDLICH LR. [en] TRAFFIC EVENTS MODELING BASED ON CLIPPING OF HUGE QUANTITY OF DATA FROM THE WEB. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2015. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23940.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

REDLICH LR. [en] TRAFFIC EVENTS MODELING BASED ON CLIPPING OF HUGE QUANTITY OF DATA FROM THE WEB. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2015. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=23940

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

26. MIGUEL MENDES DE BRITO. [en] DEEP LEARNING APPLIED TO TEXT CHUNKING.

Degree: 2019, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=38016

►

[pt] O Processamento de Linguagem natural é uma área de pesquisa que explora como computadores podem entender e manipular textos em linguagem natural. Dentre as… (more)

▼

[pt] O Processamento de Linguagem natural é uma área de pesquisa que explora como computadores podem entender e manipular textos em linguagem natural. Dentre as tarefas mais conhecidas em PLN está a de rotular sequências de texto. O problema de segmentação de texto em sintagmas é um dos problemas que pode ser abordado como rotulagem de sequências. Para isto, classificamos quais palavras pertencem a um sintagma, onde cada sintagma representa um grupo disjunto de palavras sintaticamente correlacionadas. Este tipo de segmentação possui importantes aplicações em tarefas mais complexas de processamento de linguagem natural, como análise de dependências, tradução automática, anotação de papéis semânticos, identificação de orações e outras. O objetivo deste trabalho é apresentar uma arquitetura de rede neural profunda para o problema de segmentação textual em sintagmas para a língua portuguesa. O corpus usado nos experimentos é o Bosque, do projeto Floresta Sintá(c)tica. Baseado em trabalhos recentes na área, nossa abordagem supera o estado-da-arte para o português ao alcançar um F(beta)=1 de 90,51, que corresponde a um aumento de 2,56 em comparação com o trabalho anterior. Além disso, como forma de comprovar a qualidade do segmentador, usamos os rótulos obtidos pelo nosso sistema como um dos atributos de entrada para a tarefa de análise de dependências. Esses atributos melhoraram a acurácia do analisador em 0,87.

[en] Natural Language Processing is a research field that explores how computers can understand and manipulate natural language texts. Sequence tagging is amongst the most well-known tasks in NLP. Text Chunking is one of the problems that can be approached as a sequence tagging problem. Thus, we classify which words belong to a chunk, where each chunk represents a disjoint group of syntactically correlated words. This type of chunking has important applications in more complex tasks of natural language processing, such as dependency parsing, machine translation, semantic role labeling, clause identification and much more. The goal of this work is to present a deep neural network archtecture for the Portuguese text chunking problem. The corpus used in the experiments is the Bosque, from the Floresta Sintá(c)tica project. Based on recent work in the field, our approach surpass the state-of-the-art for Portuguese by achieving a F(beta)=1 of 90.51, which corresponds to an increase of 2.56 in comparison with the previous work. In addition, in order to attest the chunker effectiveness we use the tags obtained by our system as feature for the depedency parsing task. These features improved the accuracy of the parser by 0.87.

Advisors/Committee Members: SERGIO COLCHER.

Subjects/Keywords: [pt] APRENDIZADO DE MAQUINA; [en] MACHINE LEARNING; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING; [pt] SEGMENTACAO TEXTUAL; [en] TEXT CHUNKING; [pt] APRENDIZADO PROFUNDO; [en] DEEP LEARNING

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

BRITO, M. M. D. (2019). [en] DEEP LEARNING APPLIED TO TEXT CHUNKING. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=38016

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

BRITO, MIGUEL MENDES DE. “[en] DEEP LEARNING APPLIED TO TEXT CHUNKING.” 2019. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=38016.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

BRITO, MIGUEL MENDES DE. “[en] DEEP LEARNING APPLIED TO TEXT CHUNKING.” 2019. Web. 21 Jan 2021.

Vancouver:

BRITO MMD. [en] DEEP LEARNING APPLIED TO TEXT CHUNKING. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2019. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=38016.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

BRITO MMD. [en] DEEP LEARNING APPLIED TO TEXT CHUNKING. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2019. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=38016

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

27. [No author]. [en] AN APPROACH TO ANSWERING NATURAL LANGUAGE QUESTIONS IN PORTUGUESE FROM ONTOLOGIES AND KNOWLEDGE BASES.

Degree: 2020, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47744

►

[pt] Nos últimos anos temos visto o crescimento do volume de dados não estruturados gerados naWeb tradicional, e por isso aWeb Semântica nasceu como um… (more)

▼

[pt] Nos últimos anos temos visto o crescimento do volume de dados não estruturados gerados naWeb tradicional, e por isso aWeb Semântica nasceu como um paradigma que se propõe a estruturar o conteúdo da Web de uma forma flexível, por meio de ontologias de domínio e o modelo RDF, tornando os computadores capazes de processar automaticamente esses dados e possibilitando a geração de mais informação e conhecimento. Mas para tornar estas informações acessíveis para usuários de outros domínios, é necessário que haja uma maneira mais conveniente de consultar estas bases de conhecimento. A área de Processamento de Linguagem Natural (PLN) forneceu ferramentas para permitir que a linguagem natural (falada ou escrita) seja um meio conveniente para realizar consultas em bases de conhecimento. Contudo, para que o uso da linguagem natural seja realmente efetivo, é necessário um método que converta uma pergunta ou pedido em linguagem natural em uma consulta estruturada. Tendo em vista este objetivo, o presente trabalho propõe uma abordagem que converte uma pergunta/pedido em Português em uma consulta estruturada na linguagem SPARQL, por meio do uso de árvores de dependências e ontologias estruturada em grafos, e que também permite o enriquecimento dos resultados das perguntas/pedidos por meio da geração de perguntas relacionadas.

[en] In recent years we have seen the growth of the volume of unstructured data generated in the traditional Web. Therefore the Semantic Web was born as a paradigm that proposes to structure the content of the Web flexibly through domain ontologies and the RDF model, making computers capable of automatically processing this data, enabling the generation of more information and knowledge. However, to make this information accessible to users in other domains, there needs to be a more convenient way of looking at these knowledge bases. The Natural Language Processing (NLP) area has provided tools to allow natural (spoken or writing) is a convenient way to perform queries in knowledge bases. However, for the use of natural language to be useful, a method is required that converts a natural language question or request into a structured query. With this objective, the present work proposes an approach that converts a question/request in Portuguese into a structured query in the SPARQL language, through the use of dependency trees and structured ontologies in graphs, and that also enables the enrichment of question/request results by generating related questions.

Advisors/Committee Members: SIMONE DINIZ JUNQUEIRA BARBOSA.

Subjects/Keywords: [pt] ONTOLOGIA; [en] ONTOLOGY; [pt] WEB SEMANTICA; [en] SEMANTIC WEB; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING; [pt] BASE DE CONHECIMENTO; [en] KNOWLEDGE BASES

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

author], [. (2020). [en] AN APPROACH TO ANSWERING NATURAL LANGUAGE QUESTIONS IN PORTUGUESE FROM ONTOLOGIES AND KNOWLEDGE BASES. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47744

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

author], [No. “[en] AN APPROACH TO ANSWERING NATURAL LANGUAGE QUESTIONS IN PORTUGUESE FROM ONTOLOGIES AND KNOWLEDGE BASES.” 2020. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47744.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

author], [No. “[en] AN APPROACH TO ANSWERING NATURAL LANGUAGE QUESTIONS IN PORTUGUESE FROM ONTOLOGIES AND KNOWLEDGE BASES.” 2020. Web. 21 Jan 2021.

Vancouver:

author] [. [en] AN APPROACH TO ANSWERING NATURAL LANGUAGE QUESTIONS IN PORTUGUESE FROM ONTOLOGIES AND KNOWLEDGE BASES. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2020. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47744.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

author] [. [en] AN APPROACH TO ANSWERING NATURAL LANGUAGE QUESTIONS IN PORTUGUESE FROM ONTOLOGIES AND KNOWLEDGE BASES. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2020. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47744

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

28. [No author]. [pt] SEGMENTAÇÃO SEMÂNTICA DE VAGAS DE EMPREGO: ESTUDO COMPARATIVO DE ALGORITMOS CLÁSSICOS DE APRENDIZADO DE MÁQUINA.

Degree: 2020, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=49087

►

[pt] Este trabalho demonstra como web mining, processamento de linguagem natural e aprendizado de máquina podem ser combinados para melhorar a compreensão de vagas de… (more)

▼

[pt] Este trabalho demonstra como web mining, processamento de linguagem natural e aprendizado de máquina podem ser combinados para melhorar a compreensão de vagas de emprego segmentando semanticamente os textos de suas descrições. Para atingir essa finalidade, foram coletados dados textuais de três grandes sites de vagas de emprego: Catho, LinkedIn e VAGAS.com.br. Baseado na literatura, este trabalho propôe uma estrutura semântica simplificada em que cada sentença da descrição da vaga de emprego pode pertencer a uma dessas classes: Responsabilidades, Requisitos, Benefícios e Outros. De posse dessa ideia, a tarefa de segmentação semântica pode ser repensada como uma segmentação de sentenças seguida de uma classificação. Usando o Python como ferramenta, são experimentadas algumas formas de construção de atributos a partir de textos, tanto léxicas quanto semânticas, e quatro algoritmos clássicos de aprendizado de máquina: Naive Bayes, Regressão Logística, Máquina de Vetores de Suporte e Floresta Aleatória. Como resultados, este trabalho traz um classificador (Regressão Logística com representação binária) com 95.58 porcento de acurácia, sem sobreajuste de modelo e sem degenerar as classificações por desbalanceio de classes, que é comparável ao estado da arte para Classificação de Texto. Esse classificador foi treinado e validado usando dados do Catho, mas foi testado também nos dados do VAGAS.com.br (88.60 porcento) e do LinkedIn (91.14 porcento), apresentando uma evidência de que seu aprendizado é generalizável para dados de outros sites. Além disso, o classificador foi usado para segmentação semântica das vagas de emprego e obteve uma métrica Pk de 3.67 porcento e uma métrica WindowDiff de 4.78 porcento, que é comparável ao estado da arte de Segmentação de Texto. Por fim, vale salientar duas contribuições indiretas deste trabalho: 1) uma estrutura para pensar e analisar vagas de emprego e 2) uma indicação de que algoritmos clássicos também podem alcançar o estado da arte e, portanto, sempre devem experimentados.

[en] This dissertation demonstrates how web mining, natural language processing, and machine learning can be combined to improve understanding of job openings by semantically segmenting the texts of their descriptions. To achieve this purpose, textual data were collected from three major job sites: Catho, LinkedIn and VAGAS.com.br. Based on the literature, this work proposes a simplified semantic structure in which each sentence of the job description can belong to one of these classes: Responsibilities, Requirements, Benefits and Others. With this idea, the semantic segmentation task can be rethought as a sentence segmentation followed by a classification. Using Python as a tool, some ways of constructing features from texts are tried out, both lexical and semantic, and four classic machine learning algorithms: Naïve Bayes, Logistic Regression, Support Vector Machine, and Random Forest. As a result, this work presents a classifier (Logistic Regression with binary representation) with 95.58 percent…

Advisors/Committee Members: EDUARDO SANY LABER.

Subjects/Keywords: [pt] APRENDIZADO DE MAQUINA; [pt] VAGA DE EMPREGO; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] MACHINE LEARNING; [en] JOB VACANCIES; [en] NATURAL LANGUAGE PROCESSING

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

author], [. (2020). [pt] SEGMENTAÇÃO SEMÂNTICA DE VAGAS DE EMPREGO: ESTUDO COMPARATIVO DE ALGORITMOS CLÁSSICOS DE APRENDIZADO DE MÁQUINA. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=49087

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

author], [No. “[pt] SEGMENTAÇÃO SEMÂNTICA DE VAGAS DE EMPREGO: ESTUDO COMPARATIVO DE ALGORITMOS CLÁSSICOS DE APRENDIZADO DE MÁQUINA.” 2020. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=49087.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

author], [No. “[pt] SEGMENTAÇÃO SEMÂNTICA DE VAGAS DE EMPREGO: ESTUDO COMPARATIVO DE ALGORITMOS CLÁSSICOS DE APRENDIZADO DE MÁQUINA.” 2020. Web. 21 Jan 2021.

Vancouver:

author] [. [pt] SEGMENTAÇÃO SEMÂNTICA DE VAGAS DE EMPREGO: ESTUDO COMPARATIVO DE ALGORITMOS CLÁSSICOS DE APRENDIZADO DE MÁQUINA. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2020. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=49087.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

author] [. [pt] SEGMENTAÇÃO SEMÂNTICA DE VAGAS DE EMPREGO: ESTUDO COMPARATIVO DE ALGORITMOS CLÁSSICOS DE APRENDIZADO DE MÁQUINA. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2020. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=49087

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

McMaster University

29. Cui, Yexin. Language Identification on Short Textual Data.

Degree: MASc, 2020, McMaster University

URL: http://hdl.handle.net/11375/25126

►

Language identification is the task of automatically detecting the languages(s) written in a text or a document given, and is also the very first step… (more)

Subjects/Keywords: Natural Language Processing; Language identification; Textual data

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cui, Y. (2020). Language Identification on Short Textual Data. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/25126

Chicago Manual of Style (16^th Edition):

Cui, Yexin. “Language Identification on Short Textual Data.” 2020. Masters Thesis, McMaster University. Accessed January 21, 2021. http://hdl.handle.net/11375/25126.

MLA Handbook (7^th Edition):

Cui, Yexin. “Language Identification on Short Textual Data.” 2020. Web. 21 Jan 2021.

Vancouver:

Cui Y. Language Identification on Short Textual Data. [Internet] [Masters thesis]. McMaster University; 2020. [cited 2021 Jan 21]. Available from: http://hdl.handle.net/11375/25126.

Council of Science Editors:

Cui Y. Language Identification on Short Textual Data. [Masters Thesis]. McMaster University; 2020. Available from: http://hdl.handle.net/11375/25126

Pontifical Catholic University of Rio de Janeiro

30. EDUARDO DE JESUS COELHO REIS. [en] MORPHOSYNTACTIC ANNOTATION BASED ON MORPHOLOGICAL CONTEXT.

Degree: 2016, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28461

►

[pt] Rotular as classes gramaticais ao longo de uma sentença - part-ofspeech tagging - é uma das primeiras tarefas de processamento de linguagem natural, fornecendo… (more)

▼

[pt] Rotular as classes gramaticais ao longo de uma sentença - part-ofspeech tagging - é uma das primeiras tarefas de processamento de linguagem natural, fornecendo atributos importantes para realizar tarefas de alta complexidade. A representação de texto a nível de palavra tem sido amplamente adotada, tanto através de uma codificação esparsa convencional, e.g. bagofwords; quanto por uma representação distribuída, como os sofisticados modelos de word-embedding usados para descrever informações sintáticas e semânticas. Um problema importante desse tipo de codificação é a carência de aspectos morfológicos. Além disso, os sistemas atuais apresentam uma precisão por token em torno de 97 por cento. Contudo, quando avaliados por sentença, apresentam um resultado mais modesto com uma taxa de acerto em torno de 55−57 por cento. Neste trabalho, nós demonstramos como utilizar n-grams para derivar automaticamente atributos esparsos e morfológicos para processamento de texto. Essa representação permite que redes neurais realizem a tarefa de POS-Tagging a partir de uma representação a nível de caractere. Além disso, introduzimos uma estratégia de regularização capaz de selecionar atributos específicos para cada neurônio. A utilização de regularização embutida em nossos modelos produz duas variantes. A primeira compartilha os n-grams selecionados globalmente entre todos os neurônios de uma camada; enquanto que a segunda opera uma seleção individual para cada neurônio, de forma que cada neurônio é sensível apenas aos n-grams que mais o estimulam. Utilizando a abordagem apresentada, nós geramos uma alta quantidade de características que representam afeições morfossintáticas relevantes baseadas a nível de caractere. Nosso POS tagger atinge a acurácia de 96, 67 por cento no corpus Mac-Morpho para o Português.

[en] Part-of-speech tagging is one of the primary stages in natural language processing, providing useful features for performing higher complexity tasks. Word level representations have been largely adopted, either through a conventional sparse codification, such as bag-of-words, or through a distributed representation, like the sophisticated word embedded models used to describe syntactic and semantic information. A central issue on these codifications is the lack of morphological aspects. In addition, recent taggers present per-token accuracies around 97 percent. However, when using a persentence metric, the good taggers show modest accuracies, scoring around 55-57 percent. In this work, we demonstrate how to use n-grams to automatically derive morphological sparse features for text processing. This representation allows neural networks to perform POS tagging from a character-level input. Additionally, we introduce a regularization strategy capable of selecting specific features for each layer unit. As a result, regarding n-grams selection, using the embedded regularization in our models produces two variants. The first one shares globally selected features among all layer units, whereas the second operates individual…

Advisors/Committee Members: RUY LUIZ MILIDIU.

Subjects/Keywords: [pt] REDES NEURAIS; [en] NEURAL NETWORKS; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING; [pt] PART OF SPEECH TAGGING; [pt] REPRESENTACAO MORFOLOGICA; [pt] N GRAMS; [pt] REGULARIZACAO ESPARSA

Record Details Similar Records Cite « Share

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

REIS, E. D. J. C. (2016). [en] MORPHOSYNTACTIC ANNOTATION BASED ON MORPHOLOGICAL CONTEXT. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28461

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

REIS, EDUARDO DE JESUS COELHO. “[en] MORPHOSYNTACTIC ANNOTATION BASED ON MORPHOLOGICAL CONTEXT.” 2016. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 21, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28461.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

REIS, EDUARDO DE JESUS COELHO. “[en] MORPHOSYNTACTIC ANNOTATION BASED ON MORPHOLOGICAL CONTEXT.” 2016. Web. 21 Jan 2021.

Vancouver:

REIS EDJC. [en] MORPHOSYNTACTIC ANNOTATION BASED ON MORPHOLOGICAL CONTEXT. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2016. [cited 2021 Jan 21]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28461.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

REIS EDJC. [en] MORPHOSYNTACTIC ANNOTATION BASED ON MORPHOLOGICAL CONTEXT. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2016. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28461

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

		in
And / Or
		in
And / Or
		in
And / Or
		in

Open Access Theses and Dissertations