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Sharp, Rebecca Reynolds – ProQuest LLC, 2017
We address the challenging task of "computational natural language inference," by which we mean bridging two or more natural language texts while also providing an explanation of how they are connected. In the context of question answering (i.e., finding short answers to natural language questions), this inference connects the question…
Descriptors: Computation, Natural Language Processing, Inferences, Questioning Techniques
Bridging Social and Semantic Computing - Design and Evaluation of User Interfaces for Hybrid Systems
Bostandjiev, Svetlin Alex I. – ProQuest LLC, 2012
The evolution of the Web brought new interesting problems to computer scientists that we loosely classify in the fields of social and semantic computing. Social computing is related to two major paradigms: computations carried out by a large amount of people in a collective intelligence fashion (i.e. wikis), and performing computations on social…
Descriptors: Web 2.0 Technologies, Semantics, Language Processing, Computer Interfaces
Ku, Chih-Hao – ProQuest LLC, 2012
Today's Internet-based crime reporting systems make timely and anonymous crime reporting possible. However, these reports also result in a rapidly growing set of unstructured text files. Complicating the problem is that the information has not been filtered or guided in a detective-led interview resulting in much irrelevant information. To…
Descriptors: Decision Support Systems, Crime, Classification, Visualization
Kazemzadeh, Abe – ProQuest LLC, 2013
This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current emotions as social signals, only humans can communicate about emotions symbolically. This symbolic communication of emotion allows us to talk about emotions that we…
Descriptors: Natural Language Processing, Psychological Patterns, Computer Simulation, Discourse Analysis
Li, Dingcheng – ProQuest LLC, 2011
Coreference resolution (CR) and entity relation detection (ERD) aim at finding predefined relations between pairs of entities in text. CR focuses on resolving identity relations while ERD focuses on detecting non-identity relations. Both CR and ERD are important as they can potentially improve other natural language processing (NLP) related tasks…
Descriptors: Information Retrieval, Form Classes (Languages), Computation, Natural Language Processing
Wu, Stephen Tze-Inn – ProQuest LLC, 2010
This thesis aims to define and extend a line of computational models for text comprehension that are humanly plausible. Since natural language is human by nature, computational models of human language will always be just that--models. To the degree that they miss out on information that humans would tap into, they may be improved by considering…
Descriptors: Comprehension, Semantics, Syntax, Short Term Memory