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 representation"”.
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Influence of Reading Proficiency on Text Representation in L1 and L2
… demonstrated that readers construct multi-level text representation while reading. According to Van Dijk and Kintsch (1983), these are the surface level, textbase level, and situation model level. The current project aimed to explore the effects of reading proficiency on level of text …
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Model-based feature construction and text representation for social media analysis
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-03-04 without embargo terms
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Hybrid ConVIRT - enhancing medical image-text representation learning of vision language models
… being addressed through advancements in image-text representation learning, as demonstrated by Hybrid-ConVIRT, which builds on contrastive learning frameworks such as ConVIRT and MedCLIP. These medical contrastive learning models trained on domain-specific datasets, have tackled issues related …
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Improving Natural Language Understanding via Contrastive Learning Methods
… and understand the semantic information from raw text or voice data. Among the previous NLU solutions, representation learning methods have recently become the mainstream, which maps textual data into low-dimensional vector spaces for downstream tasks. With the development of deep neural networks, …
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Enhancing memory access for less-skilled readers
… less-skilled readers often have an impoverished representation of text. The results of five experiments demonstrated that the addition of causality enhanced the text representation of less-skilled readers. Experiments 1-3 showed that the addition of causal information enhanced less-skilled …
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Expanding commonsense knowledge bases by learning from image tags
… that is supported by many contributors, has good representation of objects and their properties, and is visual. The collection's broad support of objects and object properties ensure the relevance and quality of the commonsense knowledge collected, while the visual focus provides a different …
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Context Aware Textual Entailment
… and additional facts become known and context changes. It is often the case that we do not know an aspect of the story with certainty but rather believe it to be the case; i.e., what we know is associated with uncertainty or ambiguity. In this research a method has been developed to …
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Representation learning of natural language and its application to language understanding and generation
… in Natural Language Processing (NLP). Language representation learning aims to encode rich information such as the syntax and semantics of the language into dense vectors. It facilitates the modeling, manipulation and analysis of natural language in computational linguistics. Existing algorithms …
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Coherent and controllable outfit generation
… described by a query sentence. Our method uses text and image embeddings to represent fashion items. We learn a multimodal embedding where the image representation for an item is close to its text representation, and use this embedding to measure item-query coherence. We then use a discriminator …
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A shallow processing approach to anaphor resolution
… of resolving anaphors in natural language texts by means of a "shallow processing" approach which exploits knowledge of syntax, semantics and local focussing as heavily as possible; it does not rely on the presence of large amounts of world or domain knowledge, which are notoriously hard to …
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Neuro-Symbolic Methods for Natural Language Inference and Question Answering
… lower level, we use neural networks to model the text representation and produce intermediate predictions, while at the higher level, we leverage symbolic operations to perform reasoning, which leads to the final prediction. We apply our neuro-symbolic models to solve the natural language …
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Improving Text Classification Using Graph-based Methods
Text classification is a fundamental natural language processing task. However, in real-world applications, class distributions are usually skewed, e.g., due to inherent class imbalance. In addition, the task difficulty changes based on the underlying language. When rich morphological structure and …
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Beyond topic-based representations for text mining
… amount of online information is natural language text: newspapers, blog articles, forum posts and comments, tweets, scientific literature, government documents, and more. While in general, all kinds of online information is useful, textual information is especially important—it is the most …
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Using Ontology-Based Approaches to Representing Speech Transcripts for Automated Speech Scoring
<p>Text representation is a process of transforming text into some formats that computer systems can use for subsequent information-related tasks such as text classification. Representing text faces two main challenges: meaningfulness of representation and unknown terms. Research has shown evidence …
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Role of semantic indexing for text classification.
The Vector Space Model (VSM) of text representation suffers a number of limitations for text classification. Firstly, the VSM is based on the Bag-Of-Words (BOW) assumption where terms from the indexing vocabulary are treated independently of one another. However, the expressiveness of natural …
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User behavior modeling: Towards solving the duality of interpretability and precision
… we estimate the latent aspect-based reliability representations of users in the forum to infer the trustworthiness of their answers. We also simultaneously learn the semantic meaning of their answers through text representations. We empirically show that the estimated behavioral representations …
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Connective ties in discourse : three ERP-studies on causal, temporal and concessive connective ties and their influence on language processing
… ties announce the need for a more complex text representation was recognized and made use of immediately (experiment 4). Additionally, a violation of the discourse relation resulted in more difficult semantic integration if a connective tie was present (experiment 2). It is therefore …
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Exploiting knowledge in NLP
… of topics, entities, concepts, and relations in text. Traditionally, statistical models have been successfully deployed for the aforementioned problems. However, the major trend so far has been: “scaling up by dumbing down”- that is, applying sophisticated statistical algorithms operating on very …
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Exploiting knowledge graphs for entity-centric prediction
As a special kind of ``big data'', text data can be regarded as data reported by human sensors. Since humans are far more intelligent than physical sensors, text data contains directly useful information and knowledge about the real world, making it possible to make predictions about real-world …
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Reprezentace textu a její vliv na kategorizaci
Diplomová práce se zabývá strojovým zpracováním textových dat. V teoretické části jsou popsány problémy související se zpracováním přirozeného jazyka a dále jsou představeny různé způsoby předzpracování a reprezentace textu. Práce se také blíže věnuje použití N-gramů jako rysů pro reprezentaci …