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 70 for “"Natural language understanding"”.
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Knowledge acquisition for natural language understanding
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01
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Deep Learning for Natural Language Understanding and Summarization
L'abstract è presente nell'allegato / the abstract is in the attachment
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Improving Natural Language Understanding via Contrastive Learning Methods
<p>Natural language understanding (NLU) is an essential but challenging task in Natural Language Processing (NLP), aiming to automatically extract and understand the semantic information from raw text or voice data. Among the previous NLU solutions, representation learning methods have recently …
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Neural attentions for natural language understanding and modeling
… use of neural attention mechanisms for improving natural language representation learning, a fundamental concept for modern natural language processing. With the proposed attention algorithms, our model made significant improvements in both language modeling and natural language understanding …
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Natural Language Understanding and Generation for Task-Oriented Dialogue
… due to both the inherent complexity of human language and task difficulty. Moreover, building such systems usually relies on large amounts of data with fine-grained annotations, and in many situations, it is difficult to obtain such data. It is thus important for dialogue systems to learn …
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Conditional Neural Language Models for Multimodal Learning and Natural Language Understanding
In this thesis we introduce conditional neural language models based on log-bilinear and recurrent neural networks with applications to multimodal learning and natural language understanding. We first introduce a LSTM encoder for learning visual-semantic embeddings for ranking the relevance of text …
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Enhancing Legal Document Processing through Natural Language Understanding and Generation techniques
L'abstract è presente nell'allegato / the abstract is in the attachment
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Data quality in the deep learning era: Active semi-supervised learning and text normalization for natural language understanding
… Extraction (IE) tools rely on accurate understanding of text and struggle with the noisy and informal nature of social media due to high out-of-vocabulary (OOV) word rates. In this work, we design a social media text normalization hybrid word-character attention-based encoder-decoder …
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Disabled person's control, communication and entertainment aid: an investigation of the feasibility of using speech control and natural language understanding to control a manipulator and a software application and development environment
… problems of applying speech control and natural language understanding techniques to the use of a computer by a physically disabled person. Solutions are proposed for the overcoming of some of the difficulties and limitations of the available equipment, and guidance given for the …
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Evaluation of Natural Language Processors
Despite a large amount of research on developing natural language understanding programs, little work has been done on evaluating their performance or potential. The evaluations that have been done have been unsystematic and incomplete. This has lead to uncertainty and confusion over the …
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An Intelligent Agent Based Spoken Dialog System for Content Based Image Retrieval
… the lack of a systematic approach for studying natural language understanding problems. We hope to propose a method to build robust dialog systems by exploring the fundamental relationship between language and mind. We argue that an intelligent agent is necessary for building viable natural …
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A deeper look into multi-task learning ability of unified text-to-text transformer
Structure prediction (SP) tasks are important in natural language understanding in the sense that they provide complex and structured knowledge of the text. Recently, some unified text-to-text transformer models like T5 and TANL have produced competitive results on SP tasks. These models convert SP …
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Language Acquisition in a Unification-Based Grammar Processing System Using a Real-World Knowledge Base
One of the obstacles to be overcome in Natural Language Understanding is the existence of lexical gaps; that is, words or word senses which are not in the lexicon of the system. No lexicon, whether hand-coded or derived from an on-line dictionary, can ever be complete, in the sense of having …
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On lexical level matching
In many natural language understanding applications, text processing requires comparing lexical units: words, phrases, name entities and sentences. A significant amount of research has taken place in studying evaluating similarity metrics between those units. In this thesis, we summarize some …
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Extending a quantifier scope resolution algorithm by accounting for negation.
… thesis report investigates a central problem to natural language understanding, namely the problem of scope ambiguity. The types of scope ambiguities that are considered are those that are generally resolved by speakers of a given language by relaying on common knowledge. Typical of this is the …
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Understanding language through visual imagination
This thesis introduces a multimodal approach to natural language understanding by presenting a generative language-vision model that can generate videos for sentences and a comprehensive approach for using this capability to solve natural language inference, video captioning and video completion …
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Extending Wikification: Nominal discovery, nominal linking, and the grounding of nouns
… linking, and grounding are crucial steps in natural language understanding. Compared with named entities, the detection and linking of nominals are relatively little studied but essential since the grounding of nouns enriches information for humans that read documents. In this thesis, we …
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Self-Training for Natural Language Processing
… is critical for machine learning based natural language processing models. Although many large-scale corpora and standard benchmarks have been annotated and published, they cannot cover all possible applications. As a result, it is difficult to transfer models trained with public corpora …
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Pairwise embedding for event coreference resolution
… part in information extraction research and natural language understanding areas. Recently, the pre-trained language models emerging in modern Natural Language Processing (NLP) community provide a new perspective of solving classical NLP tasks. This thesis presents a novel, extensible, and …
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