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 9 of 9 for “"semantic clustering"”.
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Open Intent Generation Through Unsupervised Semantic Clustering of Task-Oriented Dialog
… This thesis analyzes a two-staged unsupervised semantic clustering and intent generation approach with multiple dataset adaptive interchangeable methods. We examine various pre-trained embeddings, scoring objectives for the number of clusters, unsupervised clustering algorithms, intent …
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Patterns of Change in Semantic Clustering in Schizophrenia Spectrum Disorders: What Can it Tell Us about the Nature of Clustering Deficits
Semantic clustering has been used as a measure of learning strategies in a number of clinical populations and has been found to be deficient in individuals with Schizophrenia, but less attention has been paid to the dynamic use of this strategy over the course of fixed-order learning trials. In the …
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Verbal Learning and Memory in Adults with Mild, Moderate and Severe Closed Head Injury
… learning trials, head injured groups used semantic clustering less than controls, but after equating groups in terms of the number of possible clustered responses the mild and moderate did not differ from severe or control groups. After a delay, the severe group used semantic clustering …
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Similarities and Differences among Commonly Used Verbal List Learning Tasks
… characteristics, serial position effects, and semantic clustering effects were compared and contrasted across measures. Correlations for similar measures within tasks were significant, but lower than would be acceptable for alternate forms use. Differences in tasks were identified in learning …
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A data driven semantic framework for clinical trial eligibility criteria
… accuracy of this process. This thesis proposes a semantic framework for intelligent match matching to determine a minimal set of eligibility criteria with maximal coverage of clinical trials. In contrast to top down existing manual standardization efforts, a bottom-up data driven approach is …
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Acquiring and Harnessing Verb Knowledge for Multilingual Natural Language Processing
… First, I investigate the potential of acquiring semantic verb classes from non-experts through manual clustering. This subsequently informs the development of a two-phase semantic dataset creation methodology, which combines semantic clustering with fine-grained semantic similarity judgments …
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Automatic identification of representative content on Twitter
… learning of Twitter's evolving vocabulary, (2) a semantic model of tweets called Tweet2vec that generates general purpose tweet embeddings used for identifying representative tweets by robust semantic clustering. The topic model performed with an average F-1 score of 0.90 across 22 different …
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Concept-based Text Clustering
… a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates …