Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 20 for “"text understanding"”.
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Natural Arabic language text understanding
The most challenging part of natural language understanding is the representation of meaning. The current representation techniques are not sufficient to resolve the ambiguities, especially when the meaning is to be used for interrogation at a later stage. Arabic language represents a challenging …
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Toward Concept-Based Text Understanding and Mining
… application that are related to concept-based text understanding and mining---semantic integration between text and databases, based on entity identification and tracking.
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The analysis and acquisition of proper names for robust text understanding
… in the analysis of unedited, naturally-occurring text. Proper Names cause problems because of their high frequency in many types of text, their poor coverage in conventional dictionaries, their importance in the text understanding process, and the complexity of their structure and the structure of …
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Qualitative and Quantitative Causes of the Experience of Affect
… potential, and resolution of comprehender's text-understanding problems. Ratings of hedonic tone (e.g., unpleasantness/pleasantness), cognitive activity (i.e., interestingness), perceived resolvedness of text-understanding problems (e.g., not resolved/resolved), and perceived peripheral …
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Disambiguating words with self-organizing maps
Today, powerful programs readily parse English text; understanding, however, is another matter. In this thesis, I take a step toward understanding by introducing CLARIFY, a program that disambiguates words. CLARIFY identifies patterns in observed word contexts, and uses these patterns to select the …
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Towards abstractive captioning of infographics
Machine understanding of text-based narratives have predominantly focused on documents with rigid hierarchical structures and sequentially ordered inputs. These inputs include documents such as news stories, encyclopedia entries, books, and many others. However, little research has focused on …
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Knowledge integration in machine reading
… task of automatically reading a corpus of texts and, from the contents, building a knowledge base that supports automated reasoning and question answering. Success at this task could fundamentally solve the knowledge acquisition bottleneck – the widely recognized problem that …
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The semantics of role labeling
… of ascribing a semantic representation to text is an important one that can help text understanding problems like textual entailment. In this thesis, we address the problem of assigning a shallow semantic representation to text. This problem is traditionally studied in the context of verbs …
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Weakly supervised aspect extraction for domain-specific texts
Aspect extraction, identifying aspects of text segments from a pre-defined set of aspects, is one of the keystones in text understanding. It benefits numerous applications, including sentiment analysis and product review summarization. Most existing aspect extraction methods heavily rely on …
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Joint Biomedical Event Extraction and Entity Linking via Iterative Collaborative Training
… extraction are two crucial tasks to support text understanding and retrieval in the biomedical domain. These two tasks intrinsically benefit each other: entity linking disambiguates the biomedical concepts by referring to external knowledge bases and the domain knowledge further provides …
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Using Dependency Parses to Augment Feature Construction for Text Mining
… unstructured information in the form of text, there is now an increased emphasis on text mining. A broad range of techniques are now used for text mining, including algorithms adapted from machine learning, NLP, computational linguistics, and data mining. Applications are also multi-fold, …
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Proposition-based summarization with a coherence-driven incremental model
… class of methods for summarization and text understanding. In this thesis, I present one such summarizer, which uses the proposition as its meaning representation. My summarizer is an implementation of Kintsch and van Dijk's model of comprehension, which uses a tree of propositions to …
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Detecting grammatical errors with treebank-induced, probabilistic parsers
… employed in other applications, for example text understanding and machine translation. At first glance, treebank-induced grammars seem to be unsuitable for grammar checking as they massively over-generate and fail to reject ungrammatical input due to their high robustness. We present three …
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Syntax-based Concept Extraction For Question Answering
… along the path from document retrieval to text understanding. As an area of research interest, it serves as a proving ground where strategies for document processing, knowledge representation, question analysis, and answer extraction may be evaluated in real world information extraction …
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Modeling and predicting trustworthiness of online textual information
… challenges in modeling trustworthiness of free-text claims. In this dissertation, I present the need for research on trustworthiness of online information and argue for going beyond structured, extraction-centric approaches to unstructured, textual evidence-driven trust modeling. The overall …
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Problem-solving recognition in scientific text
… Therefore, they play a significant role in the understanding of academic texts from the scientific domain. Capturing knowledge of such problem-solving utterances would provide a deep insight into text understanding. In this dissertation, I present the task of problem-solving recognition in …
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Phonological Representations in Language Models
… tokens derived from web-scraped orthographic text. Understanding and interpreting these models is crucial not only for advancing NLP technology but also for gaining insights into the structure of language itself. Recently, smaller language models trained on developmentally-plausible corpora …
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English complex verb constructions: identification and inference
The fundamental problem faced by automatic text understanding in Natural Language Processing (NLP) is to identify semantically related pieces of text and integrate them together to compute the meaning of the whole text. However, the principle of compositionality runs into trouble very quickly when …
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Stammaitic Activity Versus Stammaitic Chronology; Anonymity's Impact on the Legal Narrative of the Babylonian Talmud
… the anonymous Stammaitic activity to the text. The goal is not to dismiss the possibility of a Stammaitic period, or a period of heightened Stammaitic activity. Rather, it is to broaden the scope of possible chronological provenances for Stammaitic activity. Once broadened, it becomes …
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Understanding time in natural language text
Understanding time is essential to understanding events in the world. Knowing what has happened, what is happening, and what may happen in the future is critical for reasoning about those events. It is thus an important natural language processing (NLP) task to understand time. This thesis advances …