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1
Infusing Automatic Question Generation with Natural Language Understanding
Mazidi, Karen. - : University of North Texas, 2016
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2
Automatic Language Identification for Metadata Records: Measuring the Effectiveness of Various Approaches
Knudson, Ryan Charles. - : University of North Texas, 2015
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3
Co-Training for Topic Classification of Scholarly Data
In: 2015 Conference on Empirical Methods in Natural Language Processing, September 17-21, 2015. Lisbon, Portugal. (2015)
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4
Exploration of Visual, Acoustic, and Physiological Modalities to Complement Linguistic Representations for Sentiment Analysis
Pérez-Rosas, Verónica. - : University of North Texas, 2014
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5
Multilingual Word Sense Disambiguation Using Wikipedia
Dandala, Bharath. - : University of North Texas, 2013
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6
Modeling Alcohol Consumption Using Blog Data
Koh, Kok Chuan. - : University of North Texas, 2013
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7
Extrapolating Subjectivity Research to Other Languages
Banea, Carmen. - : University of North Texas, 2013
Abstract: Socrates articulated it best, "Speak, so I may see you." Indeed, language represents an invisible probe into the mind. It is the medium through which we express our deepest thoughts, our aspirations, our views, our feelings, our inner reality. From the beginning of artificial intelligence, researchers have sought to impart human like understanding to machines. As much of our language represents a form of self expression, capturing thoughts, beliefs, evaluations, opinions, and emotions which are not available for scrutiny by an outside observer, in the field of natural language, research involving these aspects has crystallized under the name of subjectivity and sentiment analysis. While subjectivity classification labels text as either subjective or objective, sentiment classification further divides subjective text into either positive, negative or neutral. In this thesis, I investigate techniques of generating tools and resources for subjectivity analysis that do not rely on an existing natural language processing infrastructure in a given language. This constraint is motivated by the fact that the vast majority of human languages are scarce from an electronic point of view: they lack basic tools such as part-of-speech taggers, parsers, or basic resources such as electronic text, annotated corpora or lexica. This severely limits the implementation of techniques on par with those developed for English, and by applying methods that are lighter in the usage of text processing infrastructure, we are able to conduct multilingual subjectivity research in these languages as well. Since my aim is also to minimize the amount of manual work required to develop lexica or corpora in these languages, the techniques proposed employ a lever approach, where English often acts as the donor language (the fulcrum in a lever) and allows through a relatively minimal amount of effort to establish preliminary subjectivity research in a target language.
Keyword: multilingual subjectivity; Natural language processing; subjectivity analysis
URL: http://digital.library.unt.edu/ark:/67531/metadc271777/
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8
Finding Meaning in Context Using Graph Algorithms in Mono- and Cross-lingual Settings
Sinha, Ravi Som. - : University of North Texas, 2013
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9
Sentence Similarity Analysis with Applications in Automatic Short Answer Grading
Mohler, Michael A. G.. - : University of North Texas, 2012
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10
Measuring Semantic Relatedness Using Salient Encyclopedic Concepts
Hassan, Samer. - : University of North Texas, 2011
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11
Topic Modeling on Historical Newspapers
In: Association for Computational Linguistics (ACL) Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LATECH), 2011, Portland, Oregon, United States (2011)
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12
Multilingual Subjectivity: Are More Languages Better?
In: International Conference on Computational Linguistics (COLING), 2010, Beijing, China (2010)
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13
SemEval-2010 Task 2: Cross-Lingual Lexical Substitution
In: Association for Computational Linguistics (ACL) Workshop on Semantic Evaluations (SemEval), 2010, Uppsala, Sweden (2010)
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14
Annotating and Identifying Emotions in Text
In: Intelligent Information Access, 2010. Berlin: Springer-Verlag, v. 301/2010, pp. 21-38. (2010)
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15
Text Mining for Automatic Image Tagging
In: Twenty-third Annual International Conference on Computational Linguistics (COLING), 2010, Beijing, China (2010)
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16
Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation
In: North American Chapter of the Association for Computational Linguistics Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, 2010, Los Angeles, California, United States (2010)
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17
Linguistic Ethnography: Identifying Dominant Word Classes in Text
In: Conference on Computational Linguistics and Intelligent Text Processing (CICLing), 2009, Mexico City, Mexico (2009)
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18
Combining Lexical Resources for Contextual Synonym Expansion
In: International Conference in Recent Advances in Natural Language Processing (RANLP), 2009, Borovets, Bulgaria (2009)
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19
The Decomposition of Human-Written Book Summaries
In: Conference on Computational Linguistics and Intelligent Text Processing (CICLing), 2009, Mexico City, Mexico (2009)
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20
Subjectivity Word Sense Disambiguation
In: Conference on Empirical Methods in Natural Language Processing (EMNLP), 2009, Singapore (2009)
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