subject:(data extraction)

University of Waterloo

1. Zhou, Menglan. Automated Extraction of 3D Building Windows from Mobile LiDAR Data.

Degree: 2016, University of Waterloo

► The three-dimensional (3D) city models have gained more and more attentions because of their considerable potential applications at present. In particular, the demands for Level… (more)

▼ The three-dimensional (3D) city models have gained more and more attentions because of their considerable potential applications at present. In particular, the demands for Level of Detail (LoD) building models become urgent. Mobile Laser Scanning (MLS) has supplied a brand-new technology in the acquisition and update of 3D information in urban off-terrain features, particularly for building façade details. Accordingly, generating LoD3 building models from MLS point clouds becomes a new trend in recent studies. As a consequence, a method that can accurately and automatically extract 3D windows from raw MLS point clouds is presented in this thesis. To provide solid and credible information for LoD3 building models, this automated method endeavors to identify window frames on building facades from MLS point clouds. This algorithm can typically be regarded as a stepwise procedure to interpret MLS point clouds as semantic features. A voxel-based upward-growing method is firstly applied to distinguish non-ground points from ground points. Noise is then filtered out from non-ground points by statistical analysis. In order to segment out the building facades, all the remaining non-ground points are clustered based on conditional Euclidean clustering algorithm; clusters whose density and width are over a given threshold will be designated as points for building facades. After a building façade is successfully extracted, a volumetric box is created to contain façade points so that neighbours of each point can be operated. A manipulator is finally applied according to the structural characteristics of window frames to extract the potential window points. The experimental results demonstrate that the proposed algorithm can successfully extract the rectangular or curved windows in the test datasets with promising accuracies. The 2D validation and 3D validation were both conducted in this study. In the 2D validation, the lowest F-measure of the test datasets is 0.740, and the highest can be 0.977. While in the 3D validation, the lowest correctness of the test dataset is 79.58%, and the highest can be 97.96%. After further analysis of the experimental results, it was found that, for those windows concave on walls or with curtains drawn, the performance of the proposed method was influenced. Furthermore, big holes caused by system errors in raw point clouds also had negative impacts on the proposed method. In conclusion, this thesis makes a considerable contribution to extracting 3D rectangular, irregular and arc-rounded windows from noisy MLS point clouds with high accuracy and high efficiency. It has supplied a promising method for generating LoD3 building models.

Subjects/Keywords: MLS data; building facade extraction; window extraction

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

APA (6^th Edition):

Zhou, M. (2016). Automated Extraction of 3D Building Windows from Mobile LiDAR Data. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/10342

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):

Zhou, Menglan. “Automated Extraction of 3D Building Windows from Mobile LiDAR Data.” 2016. Thesis, University of Waterloo. Accessed April 11, 2021. http://hdl.handle.net/10012/10342.

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

MLA Handbook (7^th Edition):

Zhou, Menglan. “Automated Extraction of 3D Building Windows from Mobile LiDAR Data.” 2016. Web. 11 Apr 2021.

Vancouver:

Zhou M. Automated Extraction of 3D Building Windows from Mobile LiDAR Data. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10012/10342.

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

Council of Science Editors:

Zhou M. Automated Extraction of 3D Building Windows from Mobile LiDAR Data. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/10342

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

University of Waterloo

2. Farid, Mina. Extracting and Cleaning RDF Data.

Degree: 2020, University of Waterloo

URL: http://hdl.handle.net/10012/15934

► The RDF data model has become a prevalent format to represent heterogeneous data because of its versatility. The capability of dismantling information from its native… (more)

▼ The RDF data model has become a prevalent format to represent heterogeneous data because of its versatility. The capability of dismantling information from its native formats and representing it in triple format offers a simple yet powerful way of modelling data that is obtained from multiple sources. In addition, the triple format and schema constraints of the RDF model make the RDF data easy to process as labeled, directed graphs. This graph representation of RDF data supports higher-level analytics by enabling querying using different techniques and querying languages, e.g., SPARQL. Anlaytics that require structured data are supported by transforming the graph data on-the-fly to populate the target schema that is needed for downstream analysis. These target schemas are defined by downstream applications according to their information need. The flexibility of RDF data brings two main challenges. First, the extraction of RDF data is a complex task that may involve domain expertise about the information required to be extracted for different applications. Another significant aspect of analyzing RDF data is its quality, which depends on multiple factors including the reliability of data sources and the accuracy of the extraction systems. The quality of the analysis depends mainly on the quality of the underlying data. Therefore, evaluating and improving the quality of RDF data has a direct effect on the correctness of downstream analytics. This work presents multiple approaches related to the extraction and quality evaluation of RDF data. To cope with the large amounts of data that needs to be extracted, we present DSTLR, a scalable framework to extract RDF triples from semi-structured and unstructured data sources. For rare entities that fall on the long tail of information, there may not be enough signals to support high-confidence extraction. Towards this problem, we present an approach to estimate property values for long tail entities. We also present multiple algorithms and approaches that focus on the quality of RDF data. These include discovering quality constraints from RDF data, and utilizing machine learning techniques to repair errors in RDF data.

Subjects/Keywords: rdf; data quality; information extraction

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

APA (6^th Edition):

Farid, M. (2020). Extracting and Cleaning RDF Data. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15934

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):

Farid, Mina. “Extracting and Cleaning RDF Data.” 2020. Thesis, University of Waterloo. Accessed April 11, 2021. http://hdl.handle.net/10012/15934.

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

MLA Handbook (7^th Edition):

Farid, Mina. “Extracting and Cleaning RDF Data.” 2020. Web. 11 Apr 2021.

Vancouver:

Farid M. Extracting and Cleaning RDF Data. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10012/15934.

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

Council of Science Editors:

Farid M. Extracting and Cleaning RDF Data. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15934

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

University of Manchester

3. Tran, Thy Thy. Exploiting Unlabelled Data for Relation Extraction.

Degree: 2020, University of Manchester

URL: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:327033

► Information extraction transforms unstructured text to structured by annotating semantic information on raw data. A crucial step in information extraction is relation extraction, which identifies… (more)

▼ Information extraction transforms unstructured text to structured by annotating semantic information on raw data. A crucial step in information extraction is relation extraction, which identifies semantic relationships between named entities in text. The resulting relations can be used to construct and populate knowledge bases as well as used in various applications such as information retrieval and question answering. Relation extraction has been widely studied using fully supervised learning and distantly supervised approaches, these approaches require either manually- or automatically-annotated data. In contrast, a massive amount of unlabelled texts freely available are underused. We hence focus on leveraging the unlabelled data to improve and extend relation extraction. We approach the use of unlabelled text from three directions: (i) use it for pre-training word representations, (ii) conduct unsupervised learning, and (iii) perform weak supervision. Regarding the first direction, we want to leverage syntactic information for relation extraction. Instead of directly tuning such information on a relation extraction corpus, we propose a novel graph neural model for learning syntactically-informed word representations. The proposed method allows us to enrich pretrained word representations with syntactic information rather than re-training language models from scratch as previous work. Throughout this work, we can confirm that our novel representations are beneficial for relations in two different domains. In the second direction, we study unsupervised relation extraction, which is a promising approach because it does not require manually- or automatically-labelled data. We hypothesise that inductive biases are extremely important to direct unsupervised relation extraction. We hence employ two simple methods using only entity types to infer relations. Despite their simplicity, our methods can outperform existing approaches on two popular datasets. These surprising results suggest that entity types provide a strong inductive bias for unsupervised relation extraction. The last direction is inspired by recent evidence that large-scale pretrained language models capture some sort of relational facts. We want to investigate whether these pretrained language models can serve as weak annotators. To this end, we evaluate three large pretrained language models by matching sentences against relationsâ€™ exemplars. The matching scores decide how likely a given sentence expresses a relation. The top relations are further used as weak annotations to train a relation classifier. We observe that pretrained language models are confused by highly similar relations, thus, we propose a method that models the labelling confusion to correct relation prediction. We validate the proposed method on two datasets with different characteristics, showing that it can effectively model labelling noise from our weak annotator. Overall, we illustrate that exploring the use of unlabelled data is an important step towards improving relation… Advisors/Committee Members: BATISTA-NAVARRO, RIZA THERESA RTB, Ananiadou, Sophia, Batista-Navarro, Riza Theresa.

Subjects/Keywords: Relation Extraction; Unlabelled Data

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

APA (6^th Edition):

Tran, T. T. (2020). Exploiting Unlabelled Data for Relation Extraction. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:327033

Chicago Manual of Style (16^th Edition):

Tran, Thy Thy. “Exploiting Unlabelled Data for Relation Extraction.” 2020. Doctoral Dissertation, University of Manchester. Accessed April 11, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:327033.

MLA Handbook (7^th Edition):

Tran, Thy Thy. “Exploiting Unlabelled Data for Relation Extraction.” 2020. Web. 11 Apr 2021.

Vancouver:

Tran TT. Exploiting Unlabelled Data for Relation Extraction. [Internet] [Doctoral dissertation]. University of Manchester; 2020. [cited 2021 Apr 11]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:327033.

Council of Science Editors:

Tran TT. Exploiting Unlabelled Data for Relation Extraction. [Doctoral Dissertation]. University of Manchester; 2020. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:327033

University of Manchester

4. Tran, Thy. Exploiting unlabelled data for relation extraction.

Degree: PhD, 2021, University of Manchester

URL: https://www.research.manchester.ac.uk/portal/en/theses/exploiting-unlabelled-data-for-relation-extraction(dfa41a6b-25bb-4035-9a44-ce1635cf2646).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.823301

► Information extraction transforms unstructured text to structured by annotating semantic information on raw data. A crucial step in information extraction is relation extraction, which identifies… (more)

▼ Information extraction transforms unstructured text to structured by annotating semantic information on raw data. A crucial step in information extraction is relation extraction, which identifies semantic relationships between named entities in text. The resulting relations can be used to construct and populate knowledge bases as well as used in various applications such as information retrieval and question answering. Relation extraction has been widely studied using fully supervised learning and distantly supervised approaches, these approaches require either manually- or automatically-annotated data. In contrast, a massive amount of unlabelled texts freely available are underused. We hence focus on leveraging the unlabelled data to improve and extend relation extraction. We approach the use of unlabelled text from three directions: (i) use it for pre-training word representations, (ii) conduct unsupervised learning, and (iii) perform weak supervision. Regarding the first direction, we want to leverage syntactic information for relation extraction. Instead of directly tuning such information on a relation extraction corpus, we propose a novel graph neural model for learning syntactically-informed word representations. The proposed method allows us to enrich pretrained word representations with syntactic information rather than re-training language models from scratch as previous work. Throughout this work, we can confirm that our novel representations are beneficial for relations in two different domains. In the second direction, we study unsupervised relation extraction, which is a promising approach because it does not require manually- or automatically-labelled data. We hypothesise that inductive biases are extremely important to direct unsupervised relation extraction. We hence employ two simple methods using only entity types to infer relations. Despite their simplicity, our methods can outperform existing approaches on two popular datasets. These surprising results suggest that entity types provide a strong inductive bias for unsupervised relation extraction. The last direction is inspired by recent evidence that large-scale pretrained language models capture some sort of relational facts. We want to investigate whether these pretrained language models can serve as weak annotators. To this end, we evaluate three large pretrained language models by matching sentences against relations' exemplars. The matching scores decide how likely a given sentence expresses a relation. The top relations are further used as weak annotations to train a relation classifier. We observe that pretrained language models are confused by highly similar relations, thus, we propose a method that models the labelling confusion to correct relation prediction. We validate the proposed method on two datasets with different characteristics, showing that it can effectively model labelling noise from our weak annotator. Overall, we illustrate that exploring the use of unlabelled data is an important step towards improving relation…

Subjects/Keywords: Unlabelled Data; Relation Extraction

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

APA (6^th Edition):

Tran, T. (2021). Exploiting unlabelled data for relation extraction. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/exploiting-unlabelled-data-for-relation-extraction(dfa41a6b-25bb-4035-9a44-ce1635cf2646).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.823301

Chicago Manual of Style (16^th Edition):

Tran, Thy. “Exploiting unlabelled data for relation extraction.” 2021. Doctoral Dissertation, University of Manchester. Accessed April 11, 2021. https://www.research.manchester.ac.uk/portal/en/theses/exploiting-unlabelled-data-for-relation-extraction(dfa41a6b-25bb-4035-9a44-ce1635cf2646).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.823301.

MLA Handbook (7^th Edition):

Tran, Thy. “Exploiting unlabelled data for relation extraction.” 2021. Web. 11 Apr 2021.

Vancouver:

Tran T. Exploiting unlabelled data for relation extraction. [Internet] [Doctoral dissertation]. University of Manchester; 2021. [cited 2021 Apr 11]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/exploiting-unlabelled-data-for-relation-extraction(dfa41a6b-25bb-4035-9a44-ce1635cf2646).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.823301.

Council of Science Editors:

Tran T. Exploiting unlabelled data for relation extraction. [Doctoral Dissertation]. University of Manchester; 2021. Available from: https://www.research.manchester.ac.uk/portal/en/theses/exploiting-unlabelled-data-for-relation-extraction(dfa41a6b-25bb-4035-9a44-ce1635cf2646).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.823301

University of Nairobi

5. Didas, Malekia. Holistic approach for efficient extraction of web data .

Degree: 2011, University of Nairobi

URL: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13136

► There is a tremendous growth in the volume of information available on the internet, digital libraries, new sources and company database or intranets that contain… (more)

Subjects/Keywords: Web data extraction; structured data; semi structured and unstructured data

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

APA (6^th Edition):

Didas, M. (2011). Holistic approach for efficient extraction of web data . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13136

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):

Didas, Malekia. “Holistic approach for efficient extraction of web data .” 2011. Thesis, University of Nairobi. Accessed April 11, 2021. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13136.

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

MLA Handbook (7^th Edition):

Didas, Malekia. “Holistic approach for efficient extraction of web data .” 2011. Web. 11 Apr 2021.

Vancouver:

Didas M. Holistic approach for efficient extraction of web data . [Internet] [Thesis]. University of Nairobi; 2011. [cited 2021 Apr 11]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13136.

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

Council of Science Editors:

Didas M. Holistic approach for efficient extraction of web data . [Thesis]. University of Nairobi; 2011. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/13136

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

NSYSU

6. Yang, Cheng-Ju. Image classification via successive core tensor selection procedure.

Degree: Master, Applied Mathematics, 2018, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922

► In the field of artificial intelligence, high-order tensor data have been studied and analyzed, such as the automated optical inspection and MRI. Therefore, tensor decompositions… (more)

▼ In the field of artificial intelligence, high-order tensor data have been studied and analyzed, such as the automated optical inspection and MRI. Therefore, tensor decompositions and classification algorithms have become an important research topic. In a traditional neural network or machine learning method, the classification algorithm inputs training data in the form of vectors, and the trained model can identify and classify the testing data. In order to conform the input constraints, high-order tensor data are often expanded into high-dimensional vectors. However, it also leads to the loss of spatially related information adjacent to different orders, thus damages the performance of the classification. This thesis proposes a classification model combining non-negative Tucker decomposition and high-order tensors principal component analysis, and extracts feature core tensors successively to improve the accuracy of classification. Comparing with to neural network classifiers, we replace affine transformations with tensor transformations, which optimizes tensor projections to avoid missing information representing the spatial relationships in different orders, so that it extracts more complete features. For signal processing and medical image fields, data will lose its physical significance at negative values. So many non-negative decomposition and analysis methods have also become important research issues. The non-negative Tucker decomposition referred in this paper is one of them, and it is also one of the classic high-order extensions of non-negative matrix factorization. In the classification model, non-negative Tucker decomposition can not only maintain the non-negative physical meaning, but also can ignore the difference between same class, which makes the classification accuracy increase. This study explores the computational time cost and classification accuracy of the model. In the experiment of image recognition, the training time of the high-order tensor principal component analysis was reduced to half after combining non-negative Tucker decomposition. In terms of accuracy, the smaller the number of training data, the more pronounced the lead of our model is. Advisors/Committee Members: Yueh-Cheng Kuo (chair), Tzon-Tzer Lu (chair), Chieh-Sen Huang (chair), Tsung-Lin Lee (committee member).

Subjects/Keywords: data feature extraction; image classification; tensor decomposition

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

APA (6^th Edition):

Yang, C. (2018). Image classification via successive core tensor selection procedure. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922

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):

Yang, Cheng-Ju. “Image classification via successive core tensor selection procedure.” 2018. Thesis, NSYSU. Accessed April 11, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922.

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

MLA Handbook (7^th Edition):

Yang, Cheng-Ju. “Image classification via successive core tensor selection procedure.” 2018. Web. 11 Apr 2021.

Vancouver:

Yang C. Image classification via successive core tensor selection procedure. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Apr 11]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922.

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

Council of Science Editors:

Yang C. Image classification via successive core tensor selection procedure. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922

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

7. Pham, Thanh Van. Detection of plant characteristics and a comparison of effectiveness between 2d and 3d data visualization in supporting human perception of plant characteristics .

Degree: 2018, Texas A&M University – Corpus Christi

URL: https://tamucc-ir.tdl.org/handle/1969.6/87018

► Efficient agriculture requires the assessment of plant characteristics. A higher crop yield can be achieved with good quality plant characteristic data. In this research, a… (more)

Subjects/Keywords: Agriculture; Characteristic; Data Visualization; Feature extraction; Plant

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

APA (6^th Edition):

Pham, T. V. (2018). Detection of plant characteristics and a comparison of effectiveness between 2d and 3d data visualization in supporting human perception of plant characteristics . (Thesis). Texas A&M University – Corpus Christi. Retrieved from https://tamucc-ir.tdl.org/handle/1969.6/87018

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):

Pham, Thanh Van. “Detection of plant characteristics and a comparison of effectiveness between 2d and 3d data visualization in supporting human perception of plant characteristics .” 2018. Thesis, Texas A&M University – Corpus Christi. Accessed April 11, 2021. https://tamucc-ir.tdl.org/handle/1969.6/87018.

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

MLA Handbook (7^th Edition):

Pham, Thanh Van. “Detection of plant characteristics and a comparison of effectiveness between 2d and 3d data visualization in supporting human perception of plant characteristics .” 2018. Web. 11 Apr 2021.

Vancouver:

Pham TV. Detection of plant characteristics and a comparison of effectiveness between 2d and 3d data visualization in supporting human perception of plant characteristics . [Internet] [Thesis]. Texas A&M University – Corpus Christi; 2018. [cited 2021 Apr 11]. Available from: https://tamucc-ir.tdl.org/handle/1969.6/87018.

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

Council of Science Editors:

Pham TV. Detection of plant characteristics and a comparison of effectiveness between 2d and 3d data visualization in supporting human perception of plant characteristics . [Thesis]. Texas A&M University – Corpus Christi; 2018. Available from: https://tamucc-ir.tdl.org/handle/1969.6/87018

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

Delft University of Technology

8. Kreuk, Laura (author). Sentiment Analysis: a comparison of feature sets for social data and reviews.

Degree: 2018, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97

►

Consumers share their experiences or opinion about products or brands in various channels nowadays, for example on review websites or social media. Sentiment analysis is… (more)

▼

Consumers share their experiences or opinion about products or brands in various channels nowadays, for example on review websites or social media. Sentiment analysis is used to predict the sentiment of text from consumers about these products or brands in order to understand the tone of customers towards these products or brands. This thesis addresses sentiment analysis in the product domain on sentence level. In this thesis three data types are used which are collected by Unilever, review data which is text that contains the opinion of a customer towards a specific product. Social data, which can be tweets, Facebook messages, Instagram messages etc. and phone data which is a summary of a phone call of a customer about a specific product. When conducting sentiment analysis one solution is to extract features from the data which can be given to a machine learning algorithm together with sentiment labels given by human annotators. The machine learning algorithm will generate a classifier which can predict a label for sentences. In sentiment analysis literature it is often not clear why certain features are chosen or for which data type certain features will work well. In this research we compare the differences when using several feature sets for the different data types. We propose three feature sets for review data and three feature sets for social data. We focus on two aspects, comparing the different feature sets and comparing the data types. In our results we do not find significant differences in performance between the feature sets. The results suggest there might be feature sets which can improve sentiment analysis specifically for the data type, but a general feature set with standard features can be comparable to that result.

Computer Science | Data Science and Technology | Information Architecture

Advisors/Committee Members: Tintarev, Nava (mentor), Houben, Geert-Jan (graduation committee), Urbano Merino, Julian (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Sentiment Analysis; feature extraction; reviews; social data

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

APA (6^th Edition):

Kreuk, L. (. (2018). Sentiment Analysis: a comparison of feature sets for social data and reviews. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97

Chicago Manual of Style (16^th Edition):

Kreuk, Laura (author). “Sentiment Analysis: a comparison of feature sets for social data and reviews.” 2018. Masters Thesis, Delft University of Technology. Accessed April 11, 2021. http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97.

MLA Handbook (7^th Edition):

Kreuk, Laura (author). “Sentiment Analysis: a comparison of feature sets for social data and reviews.” 2018. Web. 11 Apr 2021.

Vancouver:

Kreuk L(. Sentiment Analysis: a comparison of feature sets for social data and reviews. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Apr 11]. Available from: http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97.

Council of Science Editors:

Kreuk L(. Sentiment Analysis: a comparison of feature sets for social data and reviews. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:eca6e7b5-a846-424b-ba44-84c060c29d97

University of Waterloo

9. Farid, Mina H. Query Optimization for On-Demand Information Extraction Tasks over Text Databases.

Degree: 2012, University of Waterloo

URL: http://hdl.handle.net/10012/6593

► Many modern applications involve analyzing large amounts of data that comes from unstructured text documents. In its original format, data contains information that, if extracted,… (more)

Subjects/Keywords: Database; Query Optimization; Information Extraction; Data Quality

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

APA (6^th Edition):

Farid, M. H. (2012). Query Optimization for On-Demand Information Extraction Tasks over Text Databases. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/6593

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):

Farid, Mina H. “Query Optimization for On-Demand Information Extraction Tasks over Text Databases.” 2012. Thesis, University of Waterloo. Accessed April 11, 2021. http://hdl.handle.net/10012/6593.

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

MLA Handbook (7^th Edition):

Farid, Mina H. “Query Optimization for On-Demand Information Extraction Tasks over Text Databases.” 2012. Web. 11 Apr 2021.

Vancouver:

Farid MH. Query Optimization for On-Demand Information Extraction Tasks over Text Databases. [Internet] [Thesis]. University of Waterloo; 2012. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10012/6593.

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

Council of Science Editors:

Farid MH. Query Optimization for On-Demand Information Extraction Tasks over Text Databases. [Thesis]. University of Waterloo; 2012. Available from: http://hdl.handle.net/10012/6593

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

University of Georgia

10. Kale, Sayali Shashikant. Tracking mental disorders across Twitter users.

Degree: 2016, University of Georgia

URL: http://hdl.handle.net/10724/35355"

► The prevalence of mental health disorders is often undetected, leading to a serious issue which continues to affect all parts of society. Recurrent psychological patterns… (more)

Subjects/Keywords: Twitter; Sentiment Analysis; Mental Health; Data Extraction

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

APA (6^th Edition):

Kale, S. S. (2016). Tracking mental disorders across Twitter users. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/35355"

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):

Kale, Sayali Shashikant. “Tracking mental disorders across Twitter users.” 2016. Thesis, University of Georgia. Accessed April 11, 2021. http://hdl.handle.net/10724/35355".

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

MLA Handbook (7^th Edition):

Kale, Sayali Shashikant. “Tracking mental disorders across Twitter users.” 2016. Web. 11 Apr 2021.

Vancouver:

Kale SS. Tracking mental disorders across Twitter users. [Internet] [Thesis]. University of Georgia; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/10724/35355".

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

Council of Science Editors:

Kale SS. Tracking mental disorders across Twitter users. [Thesis]. University of Georgia; 2016. Available from: http://hdl.handle.net/10724/35355"

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

University of Windsor

11. Peravali, Bindu. Comparative Mining of B2C Web Sites by Discovering Web Database Schemas.

Degree: MS, Computer Science, 2016, University of Windsor

URL: https://scholar.uwindsor.ca/etd/5861

► Discovering potentially useful and previously unknown historical knowledge from heterogeneous E-Commerce (B2C) web site contents to answer comparative queries such as “list all laptop prices… (more)

▼ Discovering potentially useful and previously unknown historical knowledge from heterogeneous E-Commerce (B2C) web site contents to answer comparative queries such as “list all laptop prices from Walmart and Staples between 2013 and 2015 including make, type, screen size, CPU power, year of make”, would require the difficult task of finding the schema of web documents from different web pages, extracting target information and performing web content data integration, building their virtual or physical data warehouse and mining from it. Automatic data extractors (wrappers) such as the WebOMiner system use data extraction techniques based on parsing the web page html source code into a document object model (DOM) tree, traversing the DOM for pattern discovery to recognize and extract different web data types (e.g., text, image, links, and lists). Some limitations of the existing systems include using complicated matching techniques such as tree matching, non-deterministic finite state automata (NFA), domain ontology and inability to answer complex comparative historical and derived queries. This thesis proposes building the WebOMiner_S which uses web structure and content mining approaches on the DOM¬ tree html code to simplify and make more easily extendable the WebOMiner system data extraction process. We propose to replace the use of NFA in the WebOMiner with a frequent structure finder algorithm which uses regular expression matching in Java XPATH parser with its methods to dynamically discover the most frequent structure (which is the most frequently repeated blocks in the html code represented as tags < div class = “ ′′ >) in the Dom tree. This approach eliminates the need for any supervised training or updating the wrapper for each new B2C web page making the approach simpler, more easily extendable and automated. Experiments show that the WebOMiner_S achieves a 100% precision and 100% recall in identifying the product records, 95.55% precision and 100% recall in identifying the data columns. Advisors/Committee Members: Ezeife, Christie.

Subjects/Keywords: Automatic Web Data Extraction; Data integration; Web Content Mining; Wrappers

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APA (6^th Edition):

Peravali, B. (2016). Comparative Mining of B2C Web Sites by Discovering Web Database Schemas. (Masters Thesis). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/5861

Chicago Manual of Style (16^th Edition):

Peravali, Bindu. “Comparative Mining of B2C Web Sites by Discovering Web Database Schemas.” 2016. Masters Thesis, University of Windsor. Accessed April 11, 2021. https://scholar.uwindsor.ca/etd/5861.

MLA Handbook (7^th Edition):

Peravali, Bindu. “Comparative Mining of B2C Web Sites by Discovering Web Database Schemas.” 2016. Web. 11 Apr 2021.

Vancouver:

Peravali B. Comparative Mining of B2C Web Sites by Discovering Web Database Schemas. [Internet] [Masters thesis]. University of Windsor; 2016. [cited 2021 Apr 11]. Available from: https://scholar.uwindsor.ca/etd/5861.

Council of Science Editors:

Peravali B. Comparative Mining of B2C Web Sites by Discovering Web Database Schemas. [Masters Thesis]. University of Windsor; 2016. Available from: https://scholar.uwindsor.ca/etd/5861

12. Ales, Zacharie. Extraction et partitionnement pour la recherche de régularités : application à l’analyse de dialogues : Extraction and clustering for regularities identification : application to dialogues analysis.

Degree: Docteur es, Mathématiques/Informatique, 2014, Rouen, INSA

URL: http://www.theses.fr/2014ISAM0015

►

Dans le cadre de l’aide à l’analyse de dialogues, un corpus de dialogues peut être représenté par un ensemble de tableaux d’annotations encodant les différents… (more)

▼

Dans le cadre de l’aide à l’analyse de dialogues, un corpus de dialogues peut être représenté par un ensemble de tableaux d’annotations encodant les différents énoncés des dialogues. Afin d’identifier des schémas dialogiques mis en oeuvre fréquemment, nous définissons une méthodologie en deux étapes : extraction de motifs récurrents, puis partitionnement de ces motifs en classes homogènes constituant ces régularités. Deux méthodes sont développées afin de réaliser l’extraction de motifs récurrents : LPCADC et SABRE. La première est une adaptation d’un algorithme de programmation dynamique tandis que la seconde est issue d’une modélisation formelle du problème d’extraction d’alignements locaux dans un couple de tableaux d’annotations.Le partitionnement de motifs récurrents est réalisé par diverses heuristiques de la littérature ainsi que deux formulations originales du problème de K-partitionnement sous la forme de programmes linéaires en nombres entiers. Lors d’une étude polyèdrale, nous caractérisons des facettes d’un polyèdre associé à ces formulations (notamment les inégalités de 2-partitions, les inégalités 2-chorded cycles et les inégalités de clique généralisées). Ces résultats théoriques permettent la mise en place d’un algorithme de plans coupants résolvant efficacement le problème.Nous développons le logiciel d’aide à la décision VIESA, mettant en oeuvre ces différentes méthodes et permettant leur évaluation au cours de deux expérimentations réalisées par un expert psychologue. Des régularités correspondant à des stratégies dialogiques que des extractions manuelles n’avaient pas permis d’obtenir sont ainsi identifiées.

In the context of dialogue analysis, a corpus of dialogues can be represented as a set of arrays of annotations encoding the dialogue utterances. In order to identify the frequently used dialogue schemes, we design a two-step methodology in which recurrent patterns are first extracted and then partitioned into homogenous classes constituting the regularities. Two methods are developed to extract recurrent patterns: LPCA-DC and SABRE. The former is an adaptation of a dynamic programming algorithm whereas the latter is obtained from a formal modeling of the extraction of local alignment problem in annotations arrays.The partitioning of recurrent patterns is realised using various heuristics from the literature as well as two original formulations of the K-partitioning problem in the form of mixed integer linear programs. Throughout a polyhedral study of a polyhedron associated to these formulations, facets are characterized (in particular: 2-chorded cycle inequalities, 2-partition inequalities and general clique inequalities). These theoretical results allow the establishment of an efficient cutting plane algorithm.We developed a decision support software called VIESA which implements these different methods and allows their evaluation during two experiments realised by a psychologist. Thus, regularities corresponding to dialogical strategies that previous manual extractions failed to…

Advisors/Committee Members: Vercouter, Laurent (thesis director), Gout, Christian (thesis director).

Subjects/Keywords: Extraction de régularités; K-partitionnement; Approche polyèdrale; Combinatorial optimization; Regularity extraction; Data mining

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

APA (6^th Edition):

Ales, Z. (2014). Extraction et partitionnement pour la recherche de régularités : application à l’analyse de dialogues : Extraction and clustering for regularities identification : application to dialogues analysis. (Doctoral Dissertation). Rouen, INSA. Retrieved from http://www.theses.fr/2014ISAM0015

Chicago Manual of Style (16^th Edition):

Ales, Zacharie. “Extraction et partitionnement pour la recherche de régularités : application à l’analyse de dialogues : Extraction and clustering for regularities identification : application to dialogues analysis.” 2014. Doctoral Dissertation, Rouen, INSA. Accessed April 11, 2021. http://www.theses.fr/2014ISAM0015.

MLA Handbook (7^th Edition):

Ales, Zacharie. “Extraction et partitionnement pour la recherche de régularités : application à l’analyse de dialogues : Extraction and clustering for regularities identification : application to dialogues analysis.” 2014. Web. 11 Apr 2021.

Vancouver:

Ales Z. Extraction et partitionnement pour la recherche de régularités : application à l’analyse de dialogues : Extraction and clustering for regularities identification : application to dialogues analysis. [Internet] [Doctoral dissertation]. Rouen, INSA; 2014. [cited 2021 Apr 11]. Available from: http://www.theses.fr/2014ISAM0015.

Council of Science Editors:

Ales Z. Extraction et partitionnement pour la recherche de régularités : application à l’analyse de dialogues : Extraction and clustering for regularities identification : application to dialogues analysis. [Doctoral Dissertation]. Rouen, INSA; 2014. Available from: http://www.theses.fr/2014ISAM0015

University of Oxford

13. Cheng, Wang. AMBER : a domain-aware template based system for data extraction.

Degree: PhD, 2015, University of Oxford

URL: http://ora.ox.ac.uk/objects/uuid:ff49d786-bfd8-4cd4-a69c-19e81cb95920 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667031

► The web is the greatest information source in human history, yet finding all offers for flats with gardens in London, Paris, and Berlin or all… (more)

▼ The web is the greatest information source in human history, yet finding all offers for flats with gardens in London, Paris, and Berlin or all restaurants open after a screening of the latest blockbuster remain hard tasks – as that data is not easily amenable to processing. Extracting web data into databases for easier processing has been a resource-intensive process, requiring human supervision for every source from which to extract. This has been changing with approaches that replace human annotators with automated annotations. Such approaches could be successfully applied to restricted settings such as single attribute extraction or for domains with significant redundancy among sources. Multi-attribute objects are often presented on (i) Result pages, where multiple objects are presented on a single page as lists, tables or grids, with most important attributes and a summary description, (ii) Detail pages, where each page provides a detailed list of attributes and long description for a single entity, often in rich format. Both result and detail pages are having their own advantages. Extracting objects from result pages is orders of magnitude faster than from detail pages, and the links to detail pages are often only accessible through result pages. Detail pages have a complete list of attributes and full description of the entity. Early web data extraction approaches requires manual annotations for each web site to reach high accuracy, while a number of domain independent approaches only focus on unsupervised repeated structure segmentation. The former is limited in scaling and automation, while the latter is lacked in accuracy. Recent automated data extraction systems are often informed with an ontology and a set of object and attribute recognizers, however they have focused on extracting simple objects with few attributes from single-entity pages and avoided result pages. We present an automatic ontology-based multi-attribute object extraction system AMBER, which deals with both result and detail pages, achieves very high accuracy (>96%) with zero site-specific supervision, and is able to solve practical issues that arise in real-life data extraction tasks. AMBER is also applied as an important component of DIADEM, the first automatic full-site extraction system that is able to extract structured data from different domains without site-specific supervision, and has been tested through a large-scale evaluation (>10, 000) sites. On the result page side, AMBER achieves high accuracy through a novel domain- aware, path-based template discovery algorithm, and integrates annotations for all parts of the extraction, from identifying the primary list of objects, over segment- ing the individual objects, to aligning the attributes. Yet, AMBER is able to tolerate significant noise in the annotations, by combining these annotations with a novel algorithm for finding regular structures based on XPATH expressions that capture regular tree structures. On the detail page side, AMBER integrates boilerplate removal, dynamic…

Subjects/Keywords: 006.3; Applications and algorithms; Program development and tools; data extraction; web extraction; result page analysis

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APA (6^th Edition):

Cheng, W. (2015). AMBER : a domain-aware template based system for data extraction. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:ff49d786-bfd8-4cd4-a69c-19e81cb95920 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667031

Chicago Manual of Style (16^th Edition):

Cheng, Wang. “AMBER : a domain-aware template based system for data extraction.” 2015. Doctoral Dissertation, University of Oxford. Accessed April 11, 2021. http://ora.ox.ac.uk/objects/uuid:ff49d786-bfd8-4cd4-a69c-19e81cb95920 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667031.

MLA Handbook (7^th Edition):

Cheng, Wang. “AMBER : a domain-aware template based system for data extraction.” 2015. Web. 11 Apr 2021.

Vancouver:

Cheng W. AMBER : a domain-aware template based system for data extraction. [Internet] [Doctoral dissertation]. University of Oxford; 2015. [cited 2021 Apr 11]. Available from: http://ora.ox.ac.uk/objects/uuid:ff49d786-bfd8-4cd4-a69c-19e81cb95920 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667031.

Council of Science Editors:

Cheng W. AMBER : a domain-aware template based system for data extraction. [Doctoral Dissertation]. University of Oxford; 2015. Available from: http://ora.ox.ac.uk/objects/uuid:ff49d786-bfd8-4cd4-a69c-19e81cb95920 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667031

University of Cincinnati

14. Ghanem, Amer G. Identifying Patterns of Epistemic Organization through Network-Based Analysis of Text Corpora.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2015, University of Cincinnati

URL: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448274706

► The growth of on-line textual content has exploded in recent years, creating truly massive text corpora. As the quantity of text available on- line increases,… (more)

▼ The growth of on-line textual content has exploded in recent years, creating truly massive text corpora. As the quantity of text available on- line increases, professionals from different industries such as marketing and politics are realizing the importance of extracting useful information and insights from this treasure trove of data. It is also clear, however, that doing so requires methods that go beyond those developed for classical data processing or even natural language processing. In particular, there is great need for efficient methods that can make sense of the semantic content of this data, and allows new knowledge to be inferred from it.The research in this dissertation describes a new method for identify- ing latent structures (topics) in texts through the application of community extraction techniques on associative networks of words. Since humans rep- resent knowledge in terms of associations, it is asserted that deriving top- ics from associative networks represents a more cognitively meaningful approach than using purely statistical patterns.The topic identification method proposed in this thesis is called Topic Extraction through Partitioning of Lexical Associative Networks (TExPLAN). It begins by constructing an associative network of words where the strength of their association indicates the frequency of their co-occurrence in documents. Once the word network is constructed, the algorithm proceeds in two stages. In the first stage, a partitioning of the word network takes place using a community extraction method to extract disjoint seed topics. The second stage of TExPLAN uses the connectivity of words across the boundaries of seed topics to assign a relevance measure to each word in each topic, thus generating a set of topics where each one covers all the words in the vocabulary, as is the case with LDA.The topics extracted by TExPLAN are used to define an epistemic metric space in which epistemic entities such as words, texts, documents, collections of documents, etc. can be embedded and compared. Once the dimensions are defined, the entities are visualized in two-dimensional space using multidimensional scaling. Because of its generality, the different types of entities can be analyzed jointly in the epistemic space. For this part of the thesis, we demonstrate the capabilities of the approach by applying it to the DBLP dataset, identifying similar conferences based on their locations in the epistemic space and deriving areas of interest associated with each conference. We are also able to analyze the epistemic diversity of conferences and determine which ones tend to attract more diverse authors and publications. Another part of the analysis focuses on authors and their participation in conferences. We define prominent status and answer questions about authors that have this status. We also look at the different ways an author can become prominent, and tie that to their epistemic diversity. Finally, we look at prominent authors who tend to publish documents that are relatively far from the… Advisors/Committee Members: Minai, Ali (Committee Chair).

Subjects/Keywords: Computer Science; Data Mining; Text Mining; Topic Extraction; Semantic Analysis; Community Extraction; Semantic Spaces

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

APA (6^th Edition):

Ghanem, A. G. (2015). Identifying Patterns of Epistemic Organization through Network-Based Analysis of Text Corpora. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448274706

Chicago Manual of Style (16^th Edition):

Ghanem, Amer G. “Identifying Patterns of Epistemic Organization through Network-Based Analysis of Text Corpora.” 2015. Doctoral Dissertation, University of Cincinnati. Accessed April 11, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448274706.

MLA Handbook (7^th Edition):

Ghanem, Amer G. “Identifying Patterns of Epistemic Organization through Network-Based Analysis of Text Corpora.” 2015. Web. 11 Apr 2021.

Vancouver:

Ghanem AG. Identifying Patterns of Epistemic Organization through Network-Based Analysis of Text Corpora. [Internet] [Doctoral dissertation]. University of Cincinnati; 2015. [cited 2021 Apr 11]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448274706.

Council of Science Editors:

Ghanem AG. Identifying Patterns of Epistemic Organization through Network-Based Analysis of Text Corpora. [Doctoral Dissertation]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448274706

INP Toulouse

15. Poulain, Vincent. Fusion d'images optique et radar à haute résolution pour la mise à jour de bases de données cartographiques : Fusion of high resolution optical and SAR images to update cartographic databases.

Degree: Docteur es, Signal, Image, Acoustique et Optimisation, 2010, INP Toulouse

URL: http://www.theses.fr/2010INPT0093

►

Cette thèse se situe dans le cadre de l'interprétation d'images satellite à haute résolution, et concerne plus spécifiquement la mise à jour de bases de… (more)

▼

Cette thèse se situe dans le cadre de l'interprétation d'images satellite à haute résolution, et concerne plus spécifiquement la mise à jour de bases de données cartographiques grâce à des images optique et radar à haute résolution. Cette étude présente une chaîne de traitement générique pour la création ou la mise à jour de bases de données représentant les routes ou les bâtiments en milieu urbain. En fonction des données disponibles, différents scénarios sont envisagés. Le traitement est effectué en deux étapes. D'abord nous cherchons les objets qui doivent être retirés de la base de données. La seconde étape consiste à rechercher dans les images de nouveaux objets à ajouter dans la base de données. Pour réaliser ces deux étapes, des descripteurs sont construits dans le but de caractériser les objets d'intérêt dans les images d'entrée. L'inclusion ou élimination des objets dans la base de données est basée sur un score obtenu après fusion des descripteurs dans le cadre de la théorie de Dempster-Shafer. Les résultats présentés dans cette thèse illustrent l'intérêt d'une fusion multi-capteurs. De plus l'intégration aisée de nouveaux descripteurs permet à la chaîne d'être améliorable et adaptable à d'autres objets.

This work takes place in the framework of high resolution remote sensing image analysis. It focuses on the issue of cartographic database creation or updating with optical and SAR images. The goal of this work is to build a generic processing chain to update or create a cartographic database representing roads and buildings in built-up areas. According to available data, various scenarios are foreseen. The proposed processing chain is composed of two steps. First, if a database is available, the presence of each database object is checked in the images. The second step consist of looking for new objects that should be included in the database. To determine if an object should be present in the updated database, relevant features are extracted from images in the neighborhood of the considered object. Those features are based on caracteristics of roads and buildings in SAR and optical images. The object removal/inclusion in the DB is based on a score obtained by the fusion of features in the framework of the Dempster-Shafer evidence theory. Results highlight the interest of multi sensor fusion. Moreover the chosen framework allows the easy integration of new features in the processing chain.

Advisors/Committee Members: Marthon, Philippe (thesis director), Tourneret, Jean-Yves (thesis director).

Subjects/Keywords: Traitement d'image; Fusion de données; Extraction de routes; Extraction de bâtiments; Image optique; Image RSO; Image processing; Data fusion; Road extraction; Building extraction; Optical image; SAR image

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APA (6^th Edition):

Poulain, V. (2010). Fusion d'images optique et radar à haute résolution pour la mise à jour de bases de données cartographiques : Fusion of high resolution optical and SAR images to update cartographic databases. (Doctoral Dissertation). INP Toulouse. Retrieved from http://www.theses.fr/2010INPT0093

Chicago Manual of Style (16^th Edition):

Poulain, Vincent. “Fusion d'images optique et radar à haute résolution pour la mise à jour de bases de données cartographiques : Fusion of high resolution optical and SAR images to update cartographic databases.” 2010. Doctoral Dissertation, INP Toulouse. Accessed April 11, 2021. http://www.theses.fr/2010INPT0093.

MLA Handbook (7^th Edition):

Poulain, Vincent. “Fusion d'images optique et radar à haute résolution pour la mise à jour de bases de données cartographiques : Fusion of high resolution optical and SAR images to update cartographic databases.” 2010. Web. 11 Apr 2021.

Vancouver:

Poulain V. Fusion d'images optique et radar à haute résolution pour la mise à jour de bases de données cartographiques : Fusion of high resolution optical and SAR images to update cartographic databases. [Internet] [Doctoral dissertation]. INP Toulouse; 2010. [cited 2021 Apr 11]. Available from: http://www.theses.fr/2010INPT0093.

Council of Science Editors:

Poulain V. Fusion d'images optique et radar à haute résolution pour la mise à jour de bases de données cartographiques : Fusion of high resolution optical and SAR images to update cartographic databases. [Doctoral Dissertation]. INP Toulouse; 2010. Available from: http://www.theses.fr/2010INPT0093

Vilnius Gediminas Technical University

16. Barauskas, Antanas. Duomenų gavimas iš daugialypių šaltinių ir jų struktūrizavimas.

Degree: Master, Informatics, 2014, Vilnius Gediminas Technical University

URL: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2014~D_20140619_092257-64025 ;

►

Šio darbo idėja yra Išgauti-Pertvarkyti-Įkelti (angl. ETL) principu veikiančios sistemos sukūrimas. Sistema išgauna duomenis iš skirtingo tipo šaltinių, juos tinkamai pertvarko ir tik tuomet įkelia… (more)

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Šio darbo idėja yra Išgauti-Pertvarkyti-Įkelti (angl. ETL) principu veikiančios sistemos sukūrimas. Sistema išgauna duomenis iš skirtingo tipo šaltinių, juos tinkamai pertvarko ir tik tuomet įkelia į parinktą saugojimo vietą. Išnagrinėti pagrindiniai duomenų gavimo būdai ir populiariausi šiuo metu ETL įrankiai. Sukurta debesų kompiuterija paremtos daugiakomponentinės duomenų gavimo iš daugialypių šaltinių ir jų struktūrizavimo vieningu formatu sistemos architektūra ir prototipas. Skirtingai nuo duomenis kaupiančių sistemų, ši sistema duomenis išgauna tik tuomet, kai jie reikalingi. Duomenų saugojimui naudojama grafu paremta duomenų bazė, kuri leidžia saugoti ne tik duomenis bet ir jų tarpusavio ryšių informaciją. Darbo apimtis: 48 puslapiai, 19 paveikslėlių, 10 lentelių ir 30 informacijos šaltinių.

The aim of this work is to create ETL (Extract-Transform-Load) system for data extraction from different types of data sources, proper transformation of the extracted data and loading the transformed data into the selected place of storage. The main techniques of data extraction and the most popular ETL tools available today have been analyzed. An architectural solution based on cloud computing, as well as, a prototype of the system for data extraction from multiple sources and data structurization have been created. Unlike the traditional data storing - based systems, the proposed system allows to extract data only in case it is needed for analysis. The graph database employed for data storage enables to store not only the data, but also the information about the relations of the entities. Structure: 48 pages, 19 figures, 10 tables and 30 references.

Advisors/Committee Members: Kulvietis, Genadijus (Master’s thesis supervisor), Mamčenko, Jelena (Master’s thesis reviewer), Šileikienė, Irma (Master’s thesis reviewer), Krupovnickas, Algirdas (Master’s degree committee chair), Kulvietis, Genadijus (Master’s degree committee member), Ostašius, Egidijus (Master’s degree committee member), Šileikienė, Irma (Master’s degree committee member), Mamčenko, Jelena (Master’s degree committee member), Šešok, Dmitrij (Master’s degree committee member), Krylovas, Aleksandras (Master’s degree committee member).

Subjects/Keywords: Duomenų gavimas; Duomenų pertvarkymas; Duomenų įkėlimas; Duomenų saugykla; Data extraction; Data transformation; Data loading; Data warehouse

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APA (6^th Edition):

Barauskas, Antanas. (2014). Duomenų gavimas iš daugialypių šaltinių ir jų struktūrizavimas. (Masters Thesis). Vilnius Gediminas Technical University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2014~D_20140619_092257-64025 ;

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

Chicago Manual of Style (16^th Edition):

Barauskas, Antanas. “Duomenų gavimas iš daugialypių šaltinių ir jų struktūrizavimas.” 2014. Masters Thesis, Vilnius Gediminas Technical University. Accessed April 11, 2021. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2014~D_20140619_092257-64025 ;.

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

MLA Handbook (7^th Edition):

Barauskas, Antanas. “Duomenų gavimas iš daugialypių šaltinių ir jų struktūrizavimas.” 2014. Web. 11 Apr 2021.

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

Vancouver:

Barauskas, Antanas. Duomenų gavimas iš daugialypių šaltinių ir jų struktūrizavimas. [Internet] [Masters thesis]. Vilnius Gediminas Technical University; 2014. [cited 2021 Apr 11]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2014~D_20140619_092257-64025 ;.

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

Council of Science Editors:

Barauskas, Antanas. Duomenų gavimas iš daugialypių šaltinių ir jų struktūrizavimas. [Masters Thesis]. Vilnius Gediminas Technical University; 2014. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2014~D_20140619_092257-64025 ;

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

Utah State University

17. Raza, Ali. Test Data Extraction and Comparison with Test Data Generation.

Degree: MS, Computer Science, 2011, Utah State University

URL: https://digitalcommons.usu.edu/etd/982

► Testing an integrated information system that relies on data from multiple sources can be a challenge, particularly when the data is confidential. This thesis… (more)

Subjects/Keywords: Data Integration; Data Sensitization/Anonymization; Health Informatics; Software Engineering; Test Data Extraction; Testing Data-Centric Applications; Computer Sciences

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

APA (6^th Edition):

Raza, A. (2011). Test Data Extraction and Comparison with Test Data Generation. (Masters Thesis). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/982

Chicago Manual of Style (16^th Edition):

Raza, Ali. “Test Data Extraction and Comparison with Test Data Generation.” 2011. Masters Thesis, Utah State University. Accessed April 11, 2021. https://digitalcommons.usu.edu/etd/982.

MLA Handbook (7^th Edition):

Raza, Ali. “Test Data Extraction and Comparison with Test Data Generation.” 2011. Web. 11 Apr 2021.

Vancouver:

Raza A. Test Data Extraction and Comparison with Test Data Generation. [Internet] [Masters thesis]. Utah State University; 2011. [cited 2021 Apr 11]. Available from: https://digitalcommons.usu.edu/etd/982.

Council of Science Editors:

Raza A. Test Data Extraction and Comparison with Test Data Generation. [Masters Thesis]. Utah State University; 2011. Available from: https://digitalcommons.usu.edu/etd/982

18. Patil, Preeti S. Improved extraction mechanism in ETL process for building of a data warehouse;.

Degree: Computer Sciences, 2013, INFLIBNET

URL: http://shodhganga.inflibnet.ac.in/handle/10603/7023

►

Today the Data warehouse plays an important role in decision making, data analysis, and strategic information and so on. Extraction Transformation and Loading (ETL) process… (more)

▼

Today the Data warehouse plays an important role in decision making, data analysis, and strategic information and so on. Extraction Transformation and Loading (ETL) process is used very popularly in building up of the data warehouse. In todays competitive Business world Mergers and Acquisitions are very common. It requires Extraction, Transformation and Loading of a huge amount of Organizational Data movement. This work proposed with respect to the Time and Space domains by the improvement in the extraction speed and file size. The existing approach is modified to apply both the standard methods of extraction, the Full Extraction and Incremental Extraction Procedures in the ETL Process. Though flat files have been widely used for simplification of the database file and existing systems does not provide any security for the same. In this thesis we are proposing the various security methods to apply over a flat file during the extraction process in ETL. These security methods can be highly recommended for very high sensitive data. Applications of security measures presented in this thesis are effective to reduce the possibility of the data leakage risk. To further reduce the size of the file the use of the delimited flat files rather than fixed length flat files converted from database files is suggested. Consequently results with reducing the extraction time of the data file. Such conversion proposal would certainly improve the speed of the extraction as presented in this thesis work. This work has provided preparatory inputs for the building process of Data warehouse and how ETL contributes to the major role in the building process. As these flat files are created from the database files the problems like redundancy, consistency, and more searching time does not occur and we can make use of the advantages of flat file during extraction process. This work provides security to the flat files before extraction and then it is extracted from the source to the destination system.

Appendix p. 113-118, References p. 119-133, List of publications p. 134-136

Advisors/Committee Members: Rao, Srikantha.

Subjects/Keywords: Computer Sciences; Change Data Capture; Data warehouse; Extraction Transformation and Loading Process

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

APA (6^th Edition):

Patil, P. S. (2013). Improved extraction mechanism in ETL process for building of a data warehouse;. (Thesis). INFLIBNET. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/7023

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):

Patil, Preeti S. “Improved extraction mechanism in ETL process for building of a data warehouse;.” 2013. Thesis, INFLIBNET. Accessed April 11, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/7023.

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

MLA Handbook (7^th Edition):

Patil, Preeti S. “Improved extraction mechanism in ETL process for building of a data warehouse;.” 2013. Web. 11 Apr 2021.

Vancouver:

Patil PS. Improved extraction mechanism in ETL process for building of a data warehouse;. [Internet] [Thesis]. INFLIBNET; 2013. [cited 2021 Apr 11]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/7023.

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

Council of Science Editors:

Patil PS. Improved extraction mechanism in ETL process for building of a data warehouse;. [Thesis]. INFLIBNET; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/7023

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

Uppsala University

19. Wrede, Fredrik. An Explorative Parameter Sweep: Spatial-temporal Data Mining in Stochastic Reaction-diffusion Simulations.

Degree: Biology Education Centre, 2016, Uppsala University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-280287

► Stochastic reaction-diffusion simulations has become an efficient approach for modelling spatial aspects of intracellular biochemical reaction networks. By accounting for intrinsic noise due to… (more)

Subjects/Keywords: Big data; feature extraction; clustering; stochastic reaction-diffusion simulation; spatial-temporal; data mining; cloud computing

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APA (6^th Edition):

Wrede, F. (2016). An Explorative Parameter Sweep: Spatial-temporal Data Mining in Stochastic Reaction-diffusion Simulations. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-280287

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):

Wrede, Fredrik. “An Explorative Parameter Sweep: Spatial-temporal Data Mining in Stochastic Reaction-diffusion Simulations.” 2016. Thesis, Uppsala University. Accessed April 11, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-280287.

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

MLA Handbook (7^th Edition):

Wrede, Fredrik. “An Explorative Parameter Sweep: Spatial-temporal Data Mining in Stochastic Reaction-diffusion Simulations.” 2016. Web. 11 Apr 2021.

Vancouver:

Wrede F. An Explorative Parameter Sweep: Spatial-temporal Data Mining in Stochastic Reaction-diffusion Simulations. [Internet] [Thesis]. Uppsala University; 2016. [cited 2021 Apr 11]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-280287.

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

Council of Science Editors:

Wrede F. An Explorative Parameter Sweep: Spatial-temporal Data Mining in Stochastic Reaction-diffusion Simulations. [Thesis]. Uppsala University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-280287

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

University of Sydney

20. Wang, Ying. On the visual similarity analysis and visualization of art image data .

Degree: 2014, University of Sydney

URL: http://hdl.handle.net/2123/11734

► This thesis introduces a framework for analyzing the underlying visual similarities among art images. Three types of art related images are investigated. They are: (1)… (more)

Subjects/Keywords: Visual similarity analysis; Data visualization; Art image data; Image feature extraction; Self-organizing map (SOM)

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APA (6^th Edition):

Wang, Y. (2014). On the visual similarity analysis and visualization of art image data . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/11734

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):

Wang, Ying. “On the visual similarity analysis and visualization of art image data .” 2014. Thesis, University of Sydney. Accessed April 11, 2021. http://hdl.handle.net/2123/11734.

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

MLA Handbook (7^th Edition):

Wang, Ying. “On the visual similarity analysis and visualization of art image data .” 2014. Web. 11 Apr 2021.

Vancouver:

Wang Y. On the visual similarity analysis and visualization of art image data . [Internet] [Thesis]. University of Sydney; 2014. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/2123/11734.

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

Council of Science Editors:

Wang Y. On the visual similarity analysis and visualization of art image data . [Thesis]. University of Sydney; 2014. Available from: http://hdl.handle.net/2123/11734

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

University of Alberta

21. Hasan, Maryam. Extracting Structured Knowledge from Textual Data in Software Repositories.

Degree: MS, Computing Science, 2011, University of Alberta

URL: https://era.library.ualberta.ca/files/cf95jb62q

► Software team members, as they communicate and coordinate their work with others throughout the life-cycle of their projects, generate different kinds of textual artifacts. Despite… (more)

Subjects/Keywords: Mining Software Repositories, Textual Data, Text Mining, Knowledge Extraction

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

APA (6^th Edition):

Hasan, M. (2011). Extracting Structured Knowledge from Textual Data in Software Repositories. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cf95jb62q

Chicago Manual of Style (16^th Edition):

Hasan, Maryam. “Extracting Structured Knowledge from Textual Data in Software Repositories.” 2011. Masters Thesis, University of Alberta. Accessed April 11, 2021. https://era.library.ualberta.ca/files/cf95jb62q.

MLA Handbook (7^th Edition):

Hasan, Maryam. “Extracting Structured Knowledge from Textual Data in Software Repositories.” 2011. Web. 11 Apr 2021.

Vancouver:

Hasan M. Extracting Structured Knowledge from Textual Data in Software Repositories. [Internet] [Masters thesis]. University of Alberta; 2011. [cited 2021 Apr 11]. Available from: https://era.library.ualberta.ca/files/cf95jb62q.

Council of Science Editors:

Hasan M. Extracting Structured Knowledge from Textual Data in Software Repositories. [Masters Thesis]. University of Alberta; 2011. Available from: https://era.library.ualberta.ca/files/cf95jb62q

University of Michigan

22. Chen, Zhe. Information Extraction on Para-Relational Data.

Degree: PhD, Computer Science and Engineering, 2016, University of Michigan

URL: http://hdl.handle.net/2027.42/120853

► Para-relational data (such as spreadsheets and diagrams) refers to a type of nearly relational data that shares the important qualities of relational data but does… (more)

Subjects/Keywords: information extraction; data mining; text mining; Computer Science; Engineering

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APA (6^th Edition):

Chen, Z. (2016). Information Extraction on Para-Relational Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120853

Chicago Manual of Style (16^th Edition):

Chen, Zhe. “Information Extraction on Para-Relational Data.” 2016. Doctoral Dissertation, University of Michigan. Accessed April 11, 2021. http://hdl.handle.net/2027.42/120853.

MLA Handbook (7^th Edition):

Chen, Zhe. “Information Extraction on Para-Relational Data.” 2016. Web. 11 Apr 2021.

Vancouver:

Chen Z. Information Extraction on Para-Relational Data. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/2027.42/120853.

Council of Science Editors:

Chen Z. Information Extraction on Para-Relational Data. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120853

Vanderbilt University

23. Osterman, Travis John. Extracting Detailed Tobacco Exposure From The Electronic Health Record.

Degree: MS, Biomedical Informatics, 2017, Vanderbilt University

URL: http://hdl.handle.net/1803/13004

► Lung cancer is the leading cause of cancer-related death in the United States and worldwide. Natural language processing (NLP) tools exist to determine smoking status… (more)

▼ Lung cancer is the leading cause of cancer-related death in the United States and worldwide. Natural language processing (NLP) tools exist to determine smoking status (ever-smoker vs. never-smoker) from electronic health record data, but no system to date extracts detailed smoking data needed to assess a patient’s eligibility for lung cancer screening. Here we describe the Smoking History And Pack-year Extraction System (SHAPES), a rules-based, NLP system to quantify tobacco exposure from electronic clinical notes. SHAPES was developed based on 261 patient records with 9,573 clinical notes and validated on 352 randomly selected patient records with 4,040 notes. F-measures for never-smoking status, ever-smoking status, rate of smoking, duration of smoking, quantity of cigarettes, and years quit were 0.86, 0.82, 0.79, 0.62, 0.64, and 0.61, respectively. Sixteen of 22 individuals eligible for lung cancer screening were identified (precision = 0.94, recall = 0.73). SHAPES was compared to a previously validated smoking classification system using a phenome wide association study (PheWAS). SHAPES predicted similar significant associations with 66% less sample size (10,000 vs. 35,788), and detected 411 (268%) more associations in the full dataset than when using just ever/never smoking status. Using smoking data from SHAPES, a smoking genome by environment interaction study found 57 statistically significant interactions between smoking and diseases including previously describes interactions between ischemic heart disease and rs1746537, obesity and rs10871777, and type 2 diabetes and rs2943641. These studies support the use of SHAPES for lung cancer screening and other research requiring quantitative smoking history. External validation needs to be performed prior to implementation at other medical centers. Advisors/Committee Members: Mia Levy, M.D., Ph.D. (committee member), Pierre Massion, M.D. (committee member), Josh Denny, M.D., M.S. (Committee Chair).

Subjects/Keywords: data extraction; lung cancer screening; phewas; gxe; smoking; natural language processing

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

APA (6^th Edition):

Osterman, T. J. (2017). Extracting Detailed Tobacco Exposure From The Electronic Health Record. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/13004

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):

Osterman, Travis John. “Extracting Detailed Tobacco Exposure From The Electronic Health Record.” 2017. Thesis, Vanderbilt University. Accessed April 11, 2021. http://hdl.handle.net/1803/13004.

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

MLA Handbook (7^th Edition):

Osterman, Travis John. “Extracting Detailed Tobacco Exposure From The Electronic Health Record.” 2017. Web. 11 Apr 2021.

Vancouver:

Osterman TJ. Extracting Detailed Tobacco Exposure From The Electronic Health Record. [Internet] [Thesis]. Vanderbilt University; 2017. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/1803/13004.

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

Council of Science Editors:

Osterman TJ. Extracting Detailed Tobacco Exposure From The Electronic Health Record. [Thesis]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/13004

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

University of North Texas

24. Liu, Siyuan. Learning from small data set for object recognition in mobile platforms.

Degree: 2016, University of North Texas

URL: https://digital.library.unt.edu/ark:/67531/metadc849633/

► Did you stand at a door with a bunch of keys and tried to find the right one to unlock the door? Did you hold… (more)

Subjects/Keywords: object recognition; machine learning; mobile platforms; small data set; feature extraction

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

APA (6^th Edition):

Liu, S. (2016). Learning from small data set for object recognition in mobile platforms. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc849633/

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):

Liu, Siyuan. “Learning from small data set for object recognition in mobile platforms.” 2016. Thesis, University of North Texas. Accessed April 11, 2021. https://digital.library.unt.edu/ark:/67531/metadc849633/.

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

MLA Handbook (7^th Edition):

Liu, Siyuan. “Learning from small data set for object recognition in mobile platforms.” 2016. Web. 11 Apr 2021.

Vancouver:

Liu S. Learning from small data set for object recognition in mobile platforms. [Internet] [Thesis]. University of North Texas; 2016. [cited 2021 Apr 11]. Available from: https://digital.library.unt.edu/ark:/67531/metadc849633/.

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

Council of Science Editors:

Liu S. Learning from small data set for object recognition in mobile platforms. [Thesis]. University of North Texas; 2016. Available from: https://digital.library.unt.edu/ark:/67531/metadc849633/

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

McMaster University

25. Jacob, Anand. IMPLEMENTING EFORM-BASED BASELINE RISK DATA EXTRACTION FROM HIGH QUALITY PAPERS FOR THE BRISKET DATABASE AND TOOL.

Degree: MSc, 2015, McMaster University

URL: http://hdl.handle.net/11375/17410

►

This thesis was undertaken to investigate if an eForm-based extractor interface would improve the efficiency of the baseline risk extraction process for BRiskeT (Baseline Risk… (more)

▼

This thesis was undertaken to investigate if an eForm-based extractor interface would improve the efficiency of the baseline risk extraction process for BRiskeT (Baseline Risk e-Tool). The BRiskeT database will contain the extracted baseline risk data from top prognostic research articles. BRiskeT utilizes McMaster University’s PLUS (Premium Literature Service) database to thoroughly vet articles prior to their inclusion in BRiskeT. The articles that have met inclusion criteria are then passed into the extractor interface that was developed for the purpose of this thesis, which has been called MacPrognosis. MacPrognosis displays these articles to a data extractor who fills out an electronic form which gives an overview of the baseline risk information in an article. The baseline risk information is subsequently saved to the BRiskeT database, which can then be queried according to the end user’s needs. One of the goals in switching from a paper-based extraction system to an eForm-based system was to save time in the extraction process. Another goal for MacPrognosis was to create an eForm that allowed baseline risk information to be extracted from as many disciplines as possible. To test whether MacPrognosis succeeded in saving extraction time and improving the proportion of articles from which baseline risk data could be extracted, it was subsequently utilized to extract data from a large test set of articles. The results of the extraction process were then compared with results from a previously conducted data extraction pilot utilizing a paper-based system which was created during the feasibility analysis for BRiskeT in 2012. The new eForm based extractor interface not only sped up the process of data extraction, but may also increase the proportion of articles from which data can be successfully extracted with minor future alterations when compared to a paper-based model of extraction.

Thesis

Master of Science (MSc)

Advisors/Committee Members: Iorio, Iorio, eHealth.

Subjects/Keywords: Baseline Risk; Data Extraction; Database; Primary Literature; McMaster PLUS Database

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

APA (6^th Edition):

Jacob, A. (2015). IMPLEMENTING EFORM-BASED BASELINE RISK DATA EXTRACTION FROM HIGH QUALITY PAPERS FOR THE BRISKET DATABASE AND TOOL. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/17410

Chicago Manual of Style (16^th Edition):

Jacob, Anand. “IMPLEMENTING EFORM-BASED BASELINE RISK DATA EXTRACTION FROM HIGH QUALITY PAPERS FOR THE BRISKET DATABASE AND TOOL.” 2015. Masters Thesis, McMaster University. Accessed April 11, 2021. http://hdl.handle.net/11375/17410.

MLA Handbook (7^th Edition):

Jacob, Anand. “IMPLEMENTING EFORM-BASED BASELINE RISK DATA EXTRACTION FROM HIGH QUALITY PAPERS FOR THE BRISKET DATABASE AND TOOL.” 2015. Web. 11 Apr 2021.

Vancouver:

Jacob A. IMPLEMENTING EFORM-BASED BASELINE RISK DATA EXTRACTION FROM HIGH QUALITY PAPERS FOR THE BRISKET DATABASE AND TOOL. [Internet] [Masters thesis]. McMaster University; 2015. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/11375/17410.

Council of Science Editors:

Jacob A. IMPLEMENTING EFORM-BASED BASELINE RISK DATA EXTRACTION FROM HIGH QUALITY PAPERS FOR THE BRISKET DATABASE AND TOOL. [Masters Thesis]. McMaster University; 2015. Available from: http://hdl.handle.net/11375/17410

Universidade Nova

26. Alves, Ricardo João de Freitas. Declarative approach to data extraction of web pages.

Degree: 2009, Universidade Nova

URL: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5822

►

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master… (more)

▼

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science

In the last few years, we have been witnessing a noticeable WEB evolution with the introduction of significant improvements at technological level, such as the emergence of XHTML, CSS,Javascript, and Web2.0, just to name ones. This, combined with other factors such as physical expansion of the Web, as well as its low cost, have been the great motivator for the organizations and the general public to join, with a consequent growth in the number of users and thus influencing the volume of the largest global data repository. In consequence, there was an increasing need for regular data acquisition from the WEB, and because of its frequency, length or complexity, it would only be viable to obtain through automatic extractors. However, two main difficulties are inherent to automatic extractors. First, much of the Web's information is presented in visual formats mainly directed for human reading. Secondly, the introduction of dynamic webpages, which are brought together in local memory from different sources, causing some pages not to have a source file. Therefore, this thesis proposes a new and more modern extractor, capable of supporting the Web evolution, as well as being generic, so as to be able to be used in any situation, and capable of being extended and easily adaptable to a more particular use. This project is an extension of an earlier one which had the capability of extractions on semi-structured text files. However it evolved to a modular extraction system capable of extracting data from webpages, semi-structured text files and be expanded to support other data source types. It also contains a more complete and generic validation system and a new data delivery system capable of performing the earlier deliveries as well as new generic ones. A graphical editor was also developed to support the extraction system features and to allow a domain expert without computer knowledge to create extractions with only a few simple and intuitive interactions on the rendered webpage.

Advisors/Committee Members: Pires, João.

Subjects/Keywords: Web wrappers; Web data extraction; Graphical wrapper construction

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

APA (6^th Edition):

Alves, R. J. d. F. (2009). Declarative approach to data extraction of web pages. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5822

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):

Alves, Ricardo João de Freitas. “Declarative approach to data extraction of web pages.” 2009. Thesis, Universidade Nova. Accessed April 11, 2021. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5822.

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

MLA Handbook (7^th Edition):

Alves, Ricardo João de Freitas. “Declarative approach to data extraction of web pages.” 2009. Web. 11 Apr 2021.

Vancouver:

Alves RJdF. Declarative approach to data extraction of web pages. [Internet] [Thesis]. Universidade Nova; 2009. [cited 2021 Apr 11]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5822.

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

Council of Science Editors:

Alves RJdF. Declarative approach to data extraction of web pages. [Thesis]. Universidade Nova; 2009. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/5822

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

Rice University

27. Shu, Anhei. Data Mining of Chinese Social Media.

Degree: PhD, Engineering, 2014, Rice University

URL: http://hdl.handle.net/1911/88119

► We present measurements and analysis of censorship on Weibo, a popular microblogging site in China. Since we were limited in the rate at which we… (more)

▼ We present measurements and analysis of censorship on Weibo, a popular microblogging site in China. Since we were limited in the rate at which we could download posts, we identified users likely to participate in sensitive topics and recursively followed their social contacts, biasing our search toward a subset of Weibo where we hoped to be more likely to observe censorship. Our architecture enables us to detect post deletions within one minute of the deletion event, giving us a high-fidelity view of what is being deleted by the censors and when. We found that deletions happen most heavily in the first hour after a post has been submitted. Focusing on original posts, not reposts/retweets, we observed that nearly 30% of the total deletion events occur within 5-30 minutes. Nearly 90% of the deletions happen within the first 24 hours. Leveraging our data, we also consider a variety of hypotheses about the mechanisms used by Weibo for censorship, such as the extent to which they use retrospective keyword-based censorship, and how repost/retweet popularity interacts with censorship. By leveraging natural language processing techniques we also perform a topical analysis of the deleted posts, overcoming the usage of neologisms, named entities, and informal language that typifies Chinese social media. Using Independent Component Analysis, we find that the topics where mass removal happens the fastest are those that combine events that are hot topics in Weibo as a whole (e.g., the Beijing rainstorms or a sex scandal) with themes common to sensitive posts (e.g., Beijing, government, China, and policeman). Air pollution is a pressing concern for industrialized countries. Air quality measurements and their interpretations often take on political overtones. Similar concerns reflect the our understanding of what levels of measured pollution correspond to different levels of human nuisance, impairment, or injury. In this paper, we consider air pollution metrics from four large Chinese cities (U.S. embassy/consulate data, and Chinese domestic measurements) and compare them to a large volume of discussions on Weibo (a popular Chinese microblogging system). In the city with the worst PM2.5, Beijing, we found a strong correlation (R=0.82) between Chinese use of pollution-related terms and the ambient pollution. In other Chinese cities with lower pollution, the correlation was weaker. Nonetheless, our results show that social media may be a valuable proxy measurement for pollution, which may be quite valuable when traditional measurement stations are unavailable (or whose output is censored or misreported). Advisors/Committee Members: Wallach, Daniel S. (advisor), Jermaine, Christopher M (committee member), Bronk, Chris (committee member).

Subjects/Keywords: Social network; microblog; data mining; topic extraction; censorship

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

APA (6^th Edition):

Shu, A. (2014). Data Mining of Chinese Social Media. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/88119

Chicago Manual of Style (16^th Edition):

Shu, Anhei. “Data Mining of Chinese Social Media.” 2014. Doctoral Dissertation, Rice University. Accessed April 11, 2021. http://hdl.handle.net/1911/88119.

MLA Handbook (7^th Edition):

Shu, Anhei. “Data Mining of Chinese Social Media.” 2014. Web. 11 Apr 2021.

Vancouver:

Shu A. Data Mining of Chinese Social Media. [Internet] [Doctoral dissertation]. Rice University; 2014. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/1911/88119.

Council of Science Editors:

Shu A. Data Mining of Chinese Social Media. [Doctoral Dissertation]. Rice University; 2014. Available from: http://hdl.handle.net/1911/88119

University of Victoria

28. Taherimakhsousi, Nina. Context aware face recognition.

Degree: Department of Computer Science, 2020, University of Victoria

URL: http://hdl.handle.net/1828/11441

► In common face recognition systems the recognition rate is not sufficient for today's applications, and systems only work in conditional databases and fail in unconstrained… (more)

▼ In common face recognition systems the recognition rate is not sufficient for today's applications, and systems only work in conditional databases and fail in unconstrained conditions. The problem addressed in this dissertation is how to exploit context information to enhance face recognition. Therefore, this dissertation focuses on the investigation of dynamic context management and adaptivity to: (i) improve context awareness and the exploit of the value of contextual information to enhance the recognition rate in face recognition systems, and (ii) improve the dynamic capabilities of adaptivity in face recognition systems by controlling the relevance of contextual information collecting, analyzing and searching context. Context awareness and adaptivity pose significant challenges for face recognition systems. Regarding context awareness, the first challenge addressed in this dissertation is data collection that can automatically analyze images in order to categorize and summarize contextual information. The second challenge arises from data extraction due to the big size of database of faces. Concerning adaptivity, the third challenge is to improve adaptive learning and classifier method with respect to variations. The fourth challenge, related also to adaptivity, concerns the high rate of videos generated by users from a dense urban area to decentralized cloud infrastructure. The fifth and sixth challenges concern the human's visual system in terms of contextual information in face recognition. Given these challenges, to improve context awareness and adaptivity in face recognition systems we made four contributions. First, we proposed our framework for location-based face recognition. The framework comprises location-centric image databases to recognize faces in images that have been taken at nearby locations frequently visited by individuals. Second, we defined contextual information and architectural designed for context aware face recognition systems. Third, we designed contextual information extraction algorithm with an architecture for context aware video-based face recognition, which decentralizes cloud computing on the SAVI network infrastructure. Fourth, we designed an experimental study of face recognition by humans. The experimental study provided insights into the nature of cues that the human visual system relies upon for achieving its impressive performance serving as the building blocks for the developed context aware face recognition system. Advisors/Committee Members: Muller, Hausi A. (supervisor).

Subjects/Keywords: Context Aware; Self-adaptive Systems; Dynamic context management; Data extraction

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

APA (6^th Edition):

Taherimakhsousi, N. (2020). Context aware face recognition. (Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/11441

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):

Taherimakhsousi, Nina. “Context aware face recognition.” 2020. Thesis, University of Victoria. Accessed April 11, 2021. http://hdl.handle.net/1828/11441.

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

MLA Handbook (7^th Edition):

Taherimakhsousi, Nina. “Context aware face recognition.” 2020. Web. 11 Apr 2021.

Vancouver:

Taherimakhsousi N. Context aware face recognition. [Internet] [Thesis]. University of Victoria; 2020. [cited 2021 Apr 11]. Available from: http://hdl.handle.net/1828/11441.

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

Council of Science Editors:

Taherimakhsousi N. Context aware face recognition. [Thesis]. University of Victoria; 2020. Available from: http://hdl.handle.net/1828/11441

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

29. Balan, Shilpa. A Study Of Data Informatics: Data Analysis And Knowledge Discovery Via A Novel Data Mining Algorithm.

Degree: PhD, Management Information Systems, 2014, University of Mississippi

URL: https://egrove.olemiss.edu/etd/914

► Frequent pattern mining (fpm) has become extremely popular among data mining researchers because it provides interesting and valuable patterns from large datasets. The decreasing cost… (more)

Subjects/Keywords: Collocation; Data Mining; Fpmies; Information Extraction; Business Administration, Management, and Operations

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

APA (6^th Edition):

Balan, S. (2014). A Study Of Data Informatics: Data Analysis And Knowledge Discovery Via A Novel Data Mining Algorithm. (Doctoral Dissertation). University of Mississippi. Retrieved from https://egrove.olemiss.edu/etd/914

Chicago Manual of Style (16^th Edition):

Balan, Shilpa. “A Study Of Data Informatics: Data Analysis And Knowledge Discovery Via A Novel Data Mining Algorithm.” 2014. Doctoral Dissertation, University of Mississippi. Accessed April 11, 2021. https://egrove.olemiss.edu/etd/914.

MLA Handbook (7^th Edition):

Balan, Shilpa. “A Study Of Data Informatics: Data Analysis And Knowledge Discovery Via A Novel Data Mining Algorithm.” 2014. Web. 11 Apr 2021.

Vancouver:

Balan S. A Study Of Data Informatics: Data Analysis And Knowledge Discovery Via A Novel Data Mining Algorithm. [Internet] [Doctoral dissertation]. University of Mississippi; 2014. [cited 2021 Apr 11]. Available from: https://egrove.olemiss.edu/etd/914.

Council of Science Editors:

Balan S. A Study Of Data Informatics: Data Analysis And Knowledge Discovery Via A Novel Data Mining Algorithm. [Doctoral Dissertation]. University of Mississippi; 2014. Available from: https://egrove.olemiss.edu/etd/914

University of Notre Dame

30. Alexandri Gregor Zavodny. Analysis of Large-Scale Unstructured Urban Range Scan Data</h1>.

Degree: Computer Science and Engineering, 2009, University of Notre Dame

URL: https://curate.nd.edu/show/3n203x8339h

► Efficient 3D scanning technology has led to acquisition of very large datasets for application areas as diverse as terrain and urban modeling, but relatively… (more)

Subjects/Keywords: range scan data; object extraction

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

APA (6^th Edition):

Zavodny, A. G. (2009). Analysis of Large-Scale Unstructured Urban Range Scan Data</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/3n203x8339h

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):

Zavodny, Alexandri Gregor. “Analysis of Large-Scale Unstructured Urban Range Scan Data</h1>.” 2009. Thesis, University of Notre Dame. Accessed April 11, 2021. https://curate.nd.edu/show/3n203x8339h.

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

MLA Handbook (7^th Edition):

Zavodny, Alexandri Gregor. “Analysis of Large-Scale Unstructured Urban Range Scan Data</h1>.” 2009. Web. 11 Apr 2021.

Vancouver:

Zavodny AG. Analysis of Large-Scale Unstructured Urban Range Scan Data</h1>. [Internet] [Thesis]. University of Notre Dame; 2009. [cited 2021 Apr 11]. Available from: https://curate.nd.edu/show/3n203x8339h.

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

Council of Science Editors:

Zavodny AG. Analysis of Large-Scale Unstructured Urban Range Scan Data</h1>. [Thesis]. University of Notre Dame; 2009. Available from: https://curate.nd.edu/show/3n203x8339h

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

Open Access Theses and Dissertations