subject:(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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

J B. Pattern based bootstrapping approaches For natural language processing of Morphologically rich languages;. [Internet] [Thesis]. Anna University; 2015. [cited 2021 Feb 26]. 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

2. 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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Alkhazi I. Compression-based parts-of-speech tagger for the Arabic language. [Internet] [Doctoral dissertation]. Bangor University; 2019. [cited 2021 Feb 26]. 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

3. 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…

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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 February 26, 2021. http://hdl.handle.net/1842/8926.

MLA Handbook (7^th Edition):

Konstas, Ioannis. “Joint models for concept-to-text generation.” 2014. Web. 26 Feb 2021.

Vancouver:

Konstas I. Joint models for concept-to-text generation. [Internet] [Doctoral dissertation]. University of Edinburgh; 2014. [cited 2021 Feb 26]. 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

4. 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

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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 February 26, 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. 26 Feb 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 Feb 26]. 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

5. 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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Krezolek MA. Natural Language Learning. [Internet] [Thesis]. Ryerson University; 2010. [cited 2021 Feb 26]. 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

6. 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

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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 February 26, 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. 26 Feb 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 Feb 26]. 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

7. 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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Tarkhadkar SS. Mutaimpact miner. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Feb 26]. 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

8. 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

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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 February 26, 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. 26 Feb 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 Feb 26]. 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

9. 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)

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Choe DK. Toward Solving Penn Treebank Parsing. [Internet] [Thesis]. Brown University; 2017. [cited 2021 Feb 26]. 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

10. 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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Luri Rodriguez I. Listening to the Market: Text Analysis Approaches to Consumer Research . [Internet] [Doctoral dissertation]. University of Arizona; 2020. [cited 2021 Feb 26]. 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

11. 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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Stantic D. A Unified Probabilistic Model for Aspect-Level Sentiment Analysis. [Internet] [Masters thesis]. University of Guelph; 2016. [cited 2021 Feb 26]. 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

12. 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

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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 February 26, 2021. http://hdl.handle.net/10657/3089.

MLA Handbook (7^th Edition):

Kulkarni, Akshay Bhavani Kumar 1994-. “Early Detection of Depression.” 2018. Web. 26 Feb 2021.

Vancouver:

Kulkarni ABK1. Early Detection of Depression. [Internet] [Masters thesis]. University of Houston; 2018. [cited 2021 Feb 26]. 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

13. 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

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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 February 26, 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. 26 Feb 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 Feb 26]. 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

14. 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

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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 February 26, 2021. http://hdl.handle.net/11299/181724.

MLA Handbook (7^th Edition):

Exley, Andrew. “Improvements to a Speech Repair Parser.” 2016. Web. 26 Feb 2021.

Vancouver:

Exley A. Improvements to a Speech Repair Parser. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2021 Feb 26]. 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

15. 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

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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 February 26, 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. 26 Feb 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 Feb 26]. 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

16. 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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Pink GA. Slot Filling . [Internet] [Thesis]. University of Sydney; 2017. [cited 2021 Feb 26]. 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

17. -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

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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 February 26, 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. 26 Feb 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 Feb 26]. 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

18. 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

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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 February 26, 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. 26 Feb 2021.

Vancouver:

Tausczik YR. Changing group dynamics through computerized language feedback. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Feb 26]. 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

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

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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 February 26, 2021. http://hdl.handle.net/10919/90884.

MLA Handbook (7^th Edition):

Patil, Supritha Basavaraj. “Analysis of Moving Events Using Tweets.” 2019. Web. 26 Feb 2021.

Vancouver:

Patil SB. Analysis of Moving Events Using Tweets. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 Feb 26]. 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

McMaster University

20. 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

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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 February 26, 2021. http://hdl.handle.net/11375/25126.

MLA Handbook (7^th Edition):

Cui, Yexin. “Language Identification on Short Textual Data.” 2020. Web. 26 Feb 2021.

Vancouver:

Cui Y. Language Identification on Short Textual Data. [Internet] [Masters thesis]. McMaster University; 2020. [cited 2021 Feb 26]. 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

21. Dong, Li. Learning natural language interfaces with neural models.

Degree: PhD, 2019, University of Edinburgh

URL: http://hdl.handle.net/1842/35587

► Language is the primary and most natural means of communication for humans. The learning curve of interacting with various devices and services (e.g., digital assistants,… (more)

▼ Language is the primary and most natural means of communication for humans. The learning curve of interacting with various devices and services (e.g., digital assistants, and smart appliances) would be greatly reduced if we could talk to machines using human language. However, in most cases computers can only interpret and execute formal languages. In this thesis, we focus on using neural models to build natural language interfaces which learn to map naturally worded expressions onto machineinterpretable representations. The task is challenging due to (1) structural mismatches between natural language and formal language, (2) the well-formedness of output representations, (3) lack of uncertainty information and interpretability, and (4) the model coverage for language variations. In this thesis, we develop several flexible neural architectures to address these challenges. We propose a model based on attention-enhanced encoder-decoder neural networks for natural language interfaces. Beyond sequence modeling, we propose a tree decoder to utilize the compositional nature and well-formedness of meaning representations, which recursively generates hierarchical structures in a top-down manner. To model meaning at different levels of granularity, we present a structure-aware neural architecture which decodes semantic representations following a coarse-to-fine procedure. The proposed neural models remain difficult to interpret, acting in most cases as a black box. We explore ways to estimate and interpret the model's confidence in its predictions, which we argue can provide users with immediate and meaningful feedback regarding uncertain outputs. We estimate confidence scores that indicate whether model predictions are likely to be correct. Moreover, we identify which parts of the input contribute to uncertain predictions allowing users to interpret their model. Model coverage is one of the major reasons resulting in uncertainty of natural language interfaces. Therefore, we develop a general framework to handle the many different ways natural language expresses the same information need. We leverage external resources to generate felicitous paraphrases for the input, and then feed them to a neural paraphrase scoring model which assigns higher weights to linguistic expressions most likely to yield correct answers. The model components are trained end-to-end using supervision signals provided by the target task. Experimental results show that the proposed neural models can be easily ported across tasks. Moreover, the robustness of natural language interfaces can be enhanced by considering the output well-formedness, confidence modeling, and improving model coverage.

Subjects/Keywords: natural language interface; question answering; natural language processing

7 more images…

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APA (6^th Edition):

Dong, L. (2019). Learning natural language interfaces with neural models. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/35587

Chicago Manual of Style (16^th Edition):

Dong, Li. “Learning natural language interfaces with neural models.” 2019. Doctoral Dissertation, University of Edinburgh. Accessed February 26, 2021. http://hdl.handle.net/1842/35587.

MLA Handbook (7^th Edition):

Dong, Li. “Learning natural language interfaces with neural models.” 2019. Web. 26 Feb 2021.

Vancouver:

Dong L. Learning natural language interfaces with neural models. [Internet] [Doctoral dissertation]. University of Edinburgh; 2019. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/1842/35587.

Council of Science Editors:

Dong L. Learning natural language interfaces with neural models. [Doctoral Dissertation]. University of Edinburgh; 2019. Available from: http://hdl.handle.net/1842/35587

University of Rochester

22. Naim, Iftekhar. Unsupervised alignment of natural language with video.

Degree: PhD, 2016, University of Rochester

URL: http://hdl.handle.net/1802/30614

► Today we encounter large amounts of video data, often accompanied with text descriptions (e.g., cooking videos and recipes, videos of wetlab experiments and protocols, movies… (more)

Subjects/Keywords: Alignment; Computer vision; Language and vision; Natural language processing; Video processing

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APA (6^th Edition):

Naim, I. (2016). Unsupervised alignment of natural language with video. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/30614

Chicago Manual of Style (16^th Edition):

Naim, Iftekhar. “Unsupervised alignment of natural language with video.” 2016. Doctoral Dissertation, University of Rochester. Accessed February 26, 2021. http://hdl.handle.net/1802/30614.

MLA Handbook (7^th Edition):

Naim, Iftekhar. “Unsupervised alignment of natural language with video.” 2016. Web. 26 Feb 2021.

Vancouver:

Naim I. Unsupervised alignment of natural language with video. [Internet] [Doctoral dissertation]. University of Rochester; 2016. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/1802/30614.

Council of Science Editors:

Naim I. Unsupervised alignment of natural language with video. [Doctoral Dissertation]. University of Rochester; 2016. Available from: http://hdl.handle.net/1802/30614

Hong Kong University of Science and Technology

23. Yu, Jinxing CSE. Joint embeddings of Chinese words, characters, and fine-grained subcharacter components.

Degree: 2017, Hong Kong University of Science and Technology

URL: http://repository.ust.hk/ir/Record/1783.1-93101 ; https://doi.org/10.14711/thesis-991012572162503412 ; http://repository.ust.hk/ir/bitstream/1783.1-93101/1/th_redirect.html

► Word embeddings have attracted much attention recently given their simplicity of word representation and generalization ability for a lot of downstream tasks. Different from alphabetic… (more)

Subjects/Keywords: Natural language processing (Computer science) ; Chinese language ; Data processing ; Computational linguistics

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APA (6^th Edition):

Yu, J. C. (2017). Joint embeddings of Chinese words, characters, and fine-grained subcharacter components. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-93101 ; https://doi.org/10.14711/thesis-991012572162503412 ; http://repository.ust.hk/ir/bitstream/1783.1-93101/1/th_redirect.html

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):

Yu, Jinxing CSE. “Joint embeddings of Chinese words, characters, and fine-grained subcharacter components.” 2017. Thesis, Hong Kong University of Science and Technology. Accessed February 26, 2021. http://repository.ust.hk/ir/Record/1783.1-93101 ; https://doi.org/10.14711/thesis-991012572162503412 ; http://repository.ust.hk/ir/bitstream/1783.1-93101/1/th_redirect.html.

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

MLA Handbook (7^th Edition):

Yu, Jinxing CSE. “Joint embeddings of Chinese words, characters, and fine-grained subcharacter components.” 2017. Web. 26 Feb 2021.

Vancouver:

Yu JC. Joint embeddings of Chinese words, characters, and fine-grained subcharacter components. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2017. [cited 2021 Feb 26]. Available from: http://repository.ust.hk/ir/Record/1783.1-93101 ; https://doi.org/10.14711/thesis-991012572162503412 ; http://repository.ust.hk/ir/bitstream/1783.1-93101/1/th_redirect.html.

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

Council of Science Editors:

Yu JC. Joint embeddings of Chinese words, characters, and fine-grained subcharacter components. [Thesis]. Hong Kong University of Science and Technology; 2017. Available from: http://repository.ust.hk/ir/Record/1783.1-93101 ; https://doi.org/10.14711/thesis-991012572162503412 ; http://repository.ust.hk/ir/bitstream/1783.1-93101/1/th_redirect.html

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

Universitat Politècnica de València

24. Reyes Pérez, Antonio. Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection .

Degree: 2012, Universitat Politècnica de València

URL: http://hdl.handle.net/10251/16692

► El lenguaje figurado representa una de las tareas más difíciles del procesamiento del lenguaje natural. A diferencia del lenguaje literal, el lenguaje figurado hace uso… (more)

▼ El lenguaje figurado representa una de las tareas más difíciles del procesamiento del lenguaje natural. A diferencia del lenguaje literal, el lenguaje figurado hace uso de recursos lingüísticos tales como la ironía, el humor, el sarcasmo, la metáfora, la analogía, entre otros, para comunicar significados indirectos que la mayoría de las veces no son interpretables sólo en términos de información sintáctica o semántica. Por el contrario, el lenguaje figurado refleja patrones del pensamiento que adquieren significado pleno en contextos comunicativos y sociales, lo cual hace que tanto su representación lingüística, así como su procesamiento computacional, se vuelvan tareas por demás complejas. En este contexto, en esta tesis de doctorado se aborda una problemática relacionada con el procesamiento del lenguaje figurado a partir de patrones lingüísticos. En particular, nuestros esfuerzos se centran en la creación de un sistema capaz de detectar automáticamente instancias de humor e ironía en textos extraídos de medios sociales. Nuestra hipótesis principal se basa en la premisa de que el lenguaje refleja patrones de conceptualización; es decir, al estudiar el lenguaje, estudiamos tales patrones. Por tanto, al analizar estos dos dominios del lenguaje figurado, pretendemos dar argumentos respecto a cómo la gente los concibe, y sobre todo, a cómo esa concepción hace que tanto humor como ironía sean verbalizados de una forma particular en diversos medios sociales. En este contexto, uno de nuestros mayores intereses es demostrar cómo el conocimiento que proviene del análisis de diferentes niveles de estudio lingüístico puede representar un conjunto de patrones relevantes para identificar automáticamente usos figurados del lenguaje. Cabe destacar que contrario a la mayoría de aproximaciones que se han enfocado en el estudio del lenguaje figurado, en nuestra investigación no buscamos dar argumentos basados únicamente en ejemplos prototípicos, sino en textos cuyas características Advisors/Committee Members: Rosso ., Paolo (advisor).

Subjects/Keywords: Automatic humor recognition; Irony detection; Figurative language processing; Natural language processing

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APA (6^th Edition):

Reyes Pérez, A. (2012). Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/16692

Chicago Manual of Style (16^th Edition):

Reyes Pérez, Antonio. “Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection .” 2012. Doctoral Dissertation, Universitat Politècnica de València. Accessed February 26, 2021. http://hdl.handle.net/10251/16692.

MLA Handbook (7^th Edition):

Reyes Pérez, Antonio. “Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection .” 2012. Web. 26 Feb 2021.

Vancouver:

Reyes Pérez A. Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2012. [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10251/16692.

Council of Science Editors:

Reyes Pérez A. Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection . [Doctoral Dissertation]. Universitat Politècnica de València; 2012. Available from: http://hdl.handle.net/10251/16692

25. Shindo, Hiroyuki. Statistical Induction of Tree-Generating Grammars for Natural Language Parsing : 木生成文法モデルの統計的学習による構文解析; キセイセイブンポウモデルノトウケイテキガクシュウニヨルコウブンカイセキ.

Degree: 博士(工学), Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/9194

Subjects/Keywords: natural language processing

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

APA (6^th Edition):

Shindo, H. (n.d.). Statistical Induction of Tree-Generating Grammars for Natural Language Parsing : 木生成文法モデルの統計的学習による構文解析; キセイセイブンポウモデルノトウケイテキガクシュウニヨルコウブンカイセキ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/9194

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shindo, Hiroyuki. “Statistical Induction of Tree-Generating Grammars for Natural Language Parsing : 木生成文法モデルの統計的学習による構文解析; キセイセイブンポウモデルノトウケイテキガクシュウニヨルコウブンカイセキ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed February 26, 2021. http://hdl.handle.net/10061/9194.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shindo, Hiroyuki. “Statistical Induction of Tree-Generating Grammars for Natural Language Parsing : 木生成文法モデルの統計的学習による構文解析; キセイセイブンポウモデルノトウケイテキガクシュウニヨルコウブンカイセキ.” Web. 26 Feb 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Shindo H. Statistical Induction of Tree-Generating Grammars for Natural Language Parsing : 木生成文法モデルの統計的学習による構文解析; キセイセイブンポウモデルノトウケイテキガクシュウニヨルコウブンカイセキ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10061/9194.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Shindo H. Statistical Induction of Tree-Generating Grammars for Natural Language Parsing : 木生成文法モデルの統計的学習による構文解析; キセイセイブンポウモデルノトウケイテキガクシュウニヨルコウブンカイセキ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/9194

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

26. Nakagawa, Tetsuji. Morphological analysis and corpus error detection using support vector machines : Support Vector Machineを用いた形態素解析とコーパスの誤り検出; Support vector machine オモチイタケイタイソカイセキトコーパスノアヤマリケンシュツ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/1302

Subjects/Keywords: Natural Language Processing

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

APA (6^th Edition):

Nakagawa, T. (n.d.). Morphological analysis and corpus error detection using support vector machines : Support Vector Machineを用いた形態素解析とコーパスの誤り検出; Support vector machine オモチイタケイタイソカイセキトコーパスノアヤマリケンシュツ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/1302

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nakagawa, Tetsuji. “Morphological analysis and corpus error detection using support vector machines : Support Vector Machineを用いた形態素解析とコーパスの誤り検出; Support vector machine オモチイタケイタイソカイセキトコーパスノアヤマリケンシュツ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed February 26, 2021. http://hdl.handle.net/10061/1302.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nakagawa, Tetsuji. “Morphological analysis and corpus error detection using support vector machines : Support Vector Machineを用いた形態素解析とコーパスの誤り検出; Support vector machine オモチイタケイタイソカイセキトコーパスノアヤマリケンシュツ.” Web. 26 Feb 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Nakagawa T. Morphological analysis and corpus error detection using support vector machines : Support Vector Machineを用いた形態素解析とコーパスの誤り検出; Support vector machine オモチイタケイタイソカイセキトコーパスノアヤマリケンシュツ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10061/1302.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Nakagawa T. Morphological analysis and corpus error detection using support vector machines : Support Vector Machineを用いた形態素解析とコーパスの誤り検出; Support vector machine オモチイタケイタイソカイセキトコーパスノアヤマリケンシュツ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/1302

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

27. Imaichi, Osamu. An Integrated Framework for Processing Grammatically Ill-Formed Sentences : 文法的不適格文処理のための統合的枠組み; ブンポウテキフテキカクブンショリノタメノトウゴウテキワクグミ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/2458

Subjects/Keywords: natural language processing

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

APA (6^th Edition):

Imaichi, O. (n.d.). An Integrated Framework for Processing Grammatically Ill-Formed Sentences : 文法的不適格文処理のための統合的枠組み; ブンポウテキフテキカクブンショリノタメノトウゴウテキワクグミ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/2458

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Imaichi, Osamu. “An Integrated Framework for Processing Grammatically Ill-Formed Sentences : 文法的不適格文処理のための統合的枠組み; ブンポウテキフテキカクブンショリノタメノトウゴウテキワクグミ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed February 26, 2021. http://hdl.handle.net/10061/2458.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Imaichi, Osamu. “An Integrated Framework for Processing Grammatically Ill-Formed Sentences : 文法的不適格文処理のための統合的枠組み; ブンポウテキフテキカクブンショリノタメノトウゴウテキワクグミ.” Web. 26 Feb 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Imaichi O. An Integrated Framework for Processing Grammatically Ill-Formed Sentences : 文法的不適格文処理のための統合的枠組み; ブンポウテキフテキカクブンショリノタメノトウゴウテキワクグミ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10061/2458.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Imaichi O. An Integrated Framework for Processing Grammatically Ill-Formed Sentences : 文法的不適格文処理のための統合的枠組み; ブンポウテキフテキカクブンショリノタメノトウゴウテキワクグミ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/2458

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

28. Suzuki, Jun. Kernels for Structured Data for Natural Language Processing : 構造化テキストに対するカーネルによる自然言語処理; コウゾウカテキストニタイスルカーネルニヨルシゼンゲンゴショリ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/2895

Subjects/Keywords: natural language processing

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

APA (6^th Edition):

Suzuki, J. (n.d.). Kernels for Structured Data for Natural Language Processing : 構造化テキストに対するカーネルによる自然言語処理; コウゾウカテキストニタイスルカーネルニヨルシゼンゲンゴショリ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/2895

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Suzuki, Jun. “Kernels for Structured Data for Natural Language Processing : 構造化テキストに対するカーネルによる自然言語処理; コウゾウカテキストニタイスルカーネルニヨルシゼンゲンゴショリ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed February 26, 2021. http://hdl.handle.net/10061/2895.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Suzuki, Jun. “Kernels for Structured Data for Natural Language Processing : 構造化テキストに対するカーネルによる自然言語処理; コウゾウカテキストニタイスルカーネルニヨルシゼンゲンゴショリ.” Web. 26 Feb 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Suzuki J. Kernels for Structured Data for Natural Language Processing : 構造化テキストに対するカーネルによる自然言語処理; コウゾウカテキストニタイスルカーネルニヨルシゼンゲンゴショリ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10061/2895.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Suzuki J. Kernels for Structured Data for Natural Language Processing : 構造化テキストに対するカーネルによる自然言語処理; コウゾウカテキストニタイスルカーネルニヨルシゼンゲンゴショリ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/2895

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

29. Asahara, Masayuki. Extended Statistical Model for Morphological Analysis : 形態素解析のための拡張統計モデル; ケイタイソカイセキノタメノカクチョウトウケイモデル.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/1358

Subjects/Keywords: Natural Language Processing

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

APA (6^th Edition):

Asahara, M. (n.d.). Extended Statistical Model for Morphological Analysis : 形態素解析のための拡張統計モデル; ケイタイソカイセキノタメノカクチョウトウケイモデル. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/1358

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Asahara, Masayuki. “Extended Statistical Model for Morphological Analysis : 形態素解析のための拡張統計モデル; ケイタイソカイセキノタメノカクチョウトウケイモデル.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed February 26, 2021. http://hdl.handle.net/10061/1358.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Asahara, Masayuki. “Extended Statistical Model for Morphological Analysis : 形態素解析のための拡張統計モデル; ケイタイソカイセキノタメノカクチョウトウケイモデル.” Web. 26 Feb 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Asahara M. Extended Statistical Model for Morphological Analysis : 形態素解析のための拡張統計モデル; ケイタイソカイセキノタメノカクチョウトウケイモデル. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10061/1358.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Asahara M. Extended Statistical Model for Morphological Analysis : 形態素解析のための拡張統計モデル; ケイタイソカイセキノタメノカクチョウトウケイモデル. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/1358

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

30. Taira, Hirotoshi. Text categorization using machine lerning : 機械学習を用いたテキスト分類; キカイガクシュウオモチイタテキストブンルイ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/2994

Subjects/Keywords: natural language processing

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

APA (6^th Edition):

Taira, H. (n.d.). Text categorization using machine lerning : 機械学習を用いたテキスト分類; キカイガクシュウオモチイタテキストブンルイ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/2994

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Taira, Hirotoshi. “Text categorization using machine lerning : 機械学習を用いたテキスト分類; キカイガクシュウオモチイタテキストブンルイ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed February 26, 2021. http://hdl.handle.net/10061/2994.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Taira, Hirotoshi. “Text categorization using machine lerning : 機械学習を用いたテキスト分類; キカイガクシュウオモチイタテキストブンルイ.” Web. 26 Feb 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Taira H. Text categorization using machine lerning : 機械学習を用いたテキスト分類; キカイガクシュウオモチイタテキストブンルイ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Feb 26]. Available from: http://hdl.handle.net/10061/2994.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Taira H. Text categorization using machine lerning : 機械学習を用いたテキスト分類; キカイガクシュウオモチイタテキストブンルイ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/2994

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

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Open Access Theses and Dissertations