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 29 for “"Latent semantic analysis"”.
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Parallel implementations of probabilistic latent semantic analysis on graphic processing units
Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining tasks such as retrieval, clustering, summarization, etc. PLSA involves iterative computation for a large number of parameters and may take hours or even days to process a large dataset, thus speeding up …
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Using latent semantic analysis to detect non-cognitive variables of academic performance
This thesis explores the possibilities of using latent semantic analysis to detect evidence of intrapersonal personality variables in post-secondary student essays. Determining student achievement based on non-cognitive variables is a complex process. Automated essay scoring tools are already in …
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Applying latent semantic analysis to computer assisted assessment in the Computer Science domain: a framework, a tool, and an evaluation
… the literature review of systems based on Latent Semantic Analysis (LSA), a statistical natural language processing technique that has been used for automated assessment of essays. The evaluation framework can help developers publish their results in a format that is comprehensive, …
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Methods for bibliometric analysis of research : renewable energy case study
… of terms relevant to the research field, analysis of the growth in prevalence of these terms over time, and identification of interrelationships among these terms using a technique known as Latent Semantic Analysis. These methods are applicable to the analysis of any research field, but …
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Web mining techniques for recommendation and personalization
… a mathematical framework, called the usage data analysis model, to characterise the observed co-occurrence of Web log files. In this mathematical model, the relationships between Web users and pages are expressed by a matrix-based usage data schema. On the basis of this data model, we aim to …
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The predictability problem
… oder durch die Anwendung der Latent Semantic Analysis gebildet, während die n-gram-Wortmaße allein auf den Ergebnissen von Internet-Suchmaschinen basieren. Weiterhin untersuchen wir die Rolle der Cloze-Vorhersagbarkeit in SWIFT, einem Modell der Blickkontrolle, und wägen ab, ob …
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Semantic spaces : behavior, language and word learning in the Human Speechome corpus
… Novel methods are introduced to perform Spatial Latent Semantic Analysis - extending the popular framework for topic modeling to cover behavior as well. Finally, the representation is used to analyze the inherent "spatiality" of individual words. A surprising connection is demonstrated between …
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EVALUATING DISTRIBUTED WORD REPRESENTATIONS FOR PREDICTING MISSING WORDS IN SENTENCES
… explored various state-of-the-art methods like Latent Semantic Analysis, word2vec, and GloVe to learn the distributed representation of words. Their performance was compared based on the accuracy achieved when tasked with selecting the right missing word in the sentence, given five possible …
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Predicting 30-Day Unplanned ICU Readmissions Using Deep Learning and Natural Language Processing Techniques: A MIMIC IV Data Analysis
… engineered using several methods, including Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA), and word embeddings.</p> <p>We sequentially implement three distinct Dense Neural Networks (DNNs) combined with the LightGBM gradient-boosting framework. Our model attained a 5-fold …
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Mining informative sentences in multi-product documents with PLSA
… of the product. we propose to use Probabilistic Latent Semantic Analysis (PLSA) to mine informative sentences given a single multi-product document. By applying PLSA in a multi-product document, it simultaneously solves three problems regarding to multi-product document: 1. Separate the document …
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Judgments of Learning and Retrospective Confidence Judgments: A Qualitative Exploration of Difference in Processes
… different but complementary text data analyses – Latent semantic analysis, n-gram word frequency analysis, and support vector machine analysis – to determine whether both JOLs and RCJs utilize the dual process descriptive method, or if RCJs instead only utilize target accessibility. Results …
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Análise de grafos de textos literários: investigação de traços psicóticos
… speech of psychotic and healthy subjects. Graph analysis of these subjects’ autobiographic reports allows the quantification of psychotic speech symptoms, marked by poor, disconnected and repetitive speech. Based on a literal reevaluation of ancient texts, Julian Jaynes proposed that psychosis …
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Representing meaning: a feature-based model of object and action words
… and neurally plausible model of lexical-semantic representations, not only for words referring to concrete objects but also for words referring to actions and events using a common set of assumptions across domains. In order to do so, features of meaning are generated by naïve speakers, …
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Semantic biometrics
… extract automatically but can still be perceived semantically using human vision. It is contended that such semantic annotations are usable as soft biometric signatures, useful for identification tasks. Feature subset selection techniques are employed to compare the distinguishing ability of …
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Latent Semantic Web Service Discovery and Composition Framework
… insufficient in this context. In this paper, a latent semantic web service discovery and composition framework, addressing both discovery and composition of web services, is introduced. The framework provides a graphical visualization interface that can facilitate users in finding the desired …
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iDiary : compression, analysis, and visualization of GPS data to predict user activities
… associated with these locations are found using latent semantic analysis and then presented as a searchable diary. One of the big challenges of working with GPS data is the large amount of data that comes with it, which becomes difficult to store and analyze. This thesis solves this challenge by …
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Exposing the hidden vocal channel: Analysis of vocal expression
… This process included 1) an interactive analysis across each condition to discover its distinguishing characteristics, 2) feature selection and evaluation via unequal variance sensitivity measurements and examination of means and 2-sigma variances across conditions, and 3) iterative, …
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Digital Approaches to Troubadour Song
… melodies and to apply computational methods of analysis to identify the musical characteristics of the melodies, find patterns and relationships, and track trends in style both over time and within the works of individual authors. In this study, I first illustrate the methodology I followed to …
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Choice Blindness: The Incongruence of Intention, Action and Introspection
… their choices. Paper three applies this form of analysis of introspection and confabulation to a second corpus of reports collected within the choice blindness paradigm. In this paper we use word-frequency and latent semantic analysis (LSA) to contrast the introspective reasons given in …
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Using Ontology-Based Approaches to Representing Speech Transcripts for Automated Speech Scoring
… challenges can be resolved by using the rich semantics in ontologies. This study aims to address these challenges by using ontology-based representation and unknown term reasoning approaches in the context of content scoring of speech, which is a less explored area compared to some common ones …
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