Global ETD Search
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Showing 1 to 20 of 29 for “"topic modelling"”.
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Rimarju
… that rhyme, incorporating these phenomena with a topic modelling system which can rank and group words in terms of context. To achieve this, a rhyme detection technique is utilized, employing the use of the International Phonetic Alphabet (IPA). This approach is able to handle the challenges and …
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ADAPTIVE FRAMEWORKS FOR KNOWLEDGE EXTRACTION IN HETEROGENEOUS DATA ENVIRONMENTS
… SHIFT, the first seed-guided hierarchical topic modelling framework specifically designed for heterogeneous data environments. It combines unsupervised information extraction with advanced representation learning techniques, incorporating external knowledge bases to enhance semantic …
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Non-parametric bayesian methods for structured topic models
… several new and interesting research challenges. Topic modelling, as a promising statistical technique, has gained significant momentum in recent years in information retrieval, sentiment analysis, images processing, etc. Besides existing topic models, the field of topic modelling still needs to …
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Non-parametric bayesian methods for structured topic models
… several new and interesting research challenges. Topic modelling, as a promising statistical technique, has gained significant momentum in recent years in information retrieval, sentiment analysis, images processing, etc. Besides existing topic models, the field of topic modelling still needs to …
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Natural Language Processing methods for short informal text
… to be a challenge for many NLP methods like topic modelling, named entity recognition, and sentiment analysis. We produced novel methods in NLP that target the short text informality. Our first novel model is in topic modelling for short messy text. The proposed model was inspired by the …
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Performance analysis of text classification algorithms for PubMed articles
… several different machine learning algorithms (Topic Modelling, Random Forest, Logistic Regression, Support Vector Classifiers, Multinomial Naive Bayes, Convolutional Neural Network and Long Short-Term Memory (LSTM)) in reproducing manually assigned MeSH annotations. Records for this study were …
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Topic modeling in game reviews
… game reviews for Elden Ring were analyzed for topic modelling using Latent Dirichlet Allocation (LDA), Bidirectional Encoder Representations from Transformers (BERT), and a hybrid model combining both to identify effective methods for extracting underlying themes in player feedback. We analyzed …
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Exploring Topic Modeling in The Domain of Integrated Water Resource Management
… application of text mining techniques, namely, topic modelling, to scientific publications in the sustainable water resource management domain with the goal to identify major research questions, practical problems and methodological approaches used to address these problems. Comparative analysis …
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Structural Equation Modelling of Quality of Life in Adults with Down Syndrome in Nigeria
… Factor Analysis (CFA), Structural Equation Modelling (SEM), and Latent Dirichlet Allocation (LDA) for Topic Modelling. EFA revealed 10 factors in self-reported data and 11 in proxy-reported data, suggesting a more complex QoL structure than the hypothesised eight domains. CFA demonstrated a …
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Macroeconomic Forecasting and Market Analysis with Newspaper Articles
… macroeconomic activity. A second strand uses topic indicators, capturing variation in the intensity with which different themes are covered in the media. A third, more recent strand combines these approaches by assigning sentiment to individual topics, and therefore produces topic-specific …
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Computational Linguistic Models of Mental Spaces
… integration using Latent Dirichlet Allocation, a topic modelling algorithm. We choose three experiments with which to validate the usefulness of this approach. Our fi�rst experiment investigates text classi�cation using the Full Text corpus within FrameNet. Our second experiment uses the corpora …
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Understanding Employee Attrition Factors in the Information Technology Sector: A Text Analytics Perspective
… applied the Latent Dirichlet Allocation (LDA) topic modelling technique to find out the most cited attrition factors in the comments. We recognized that “Personal Development”, “Financial and Professional Development” and “Cultural Development” are the most frequent factors mentioned by …
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Navigating in Turbulent Times: Using Social Media Discourse to Examine Small and Family-Owned Business Survival and Government Actions During The COVID-19 Crisis
… initial part of the study uncovered the diverse topics that emerged in social media conversations concerning smaller and family-owned businesses during the pandemic, encompassing challenges faced by different demographic groups, discussions around vaccine mandates, entrepreneurial opportunities …
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Building Human Digital Twins through Natural Language Processing: From Conversations to Knowledge
… that addresses these challenges through advanced topic modelling, natural language processing, and information verification techniques. A key objective is to enhance HDTs' efficiency in capturing and organizing human knowledge from diverse conversational sources. This involves developing novel …
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Exploring the application of Natural Language Processing to scientific medical cannabis publications
… techniques (such as document clustering and topic modelling, global vector word embeddings and supervised document classifiers) are used to group 500 journal articles from the general literature on cannabis according to broad research topics; analyse the interaction between cannabis …
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Dynamic User Profiling for Search Personalisation
… A widely used type of profile represents the topical interests of the user. In these cases, a typical approach is to build a user profile using topics discussed in documents which the user has found relevant, and where the topics are obtained from a human-generated ontology or directory. …
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Digital Critical Editing, Digital Text Analysis, and Charles R. Maturin’s Melmoth the Wanderer
… available in multiple formats for analysis, by topic modelling a corpus of texts contemporary to the edition’s text and making visualisations of those topic models available to the user in the edition’s paratexts as a novel way of contextualising the edition text, and finally by allowing users …
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Building blocks for the mind
… several baselines which rely on state of the art topic modelling methods that do not enforce sparsity in the input data. In the second experiment, I obtain a new state of the art result on Sentiment Analysis and show that the trained system can now provide justification by pinpointing climactic …
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Go With the Flow: A Quantitative Analysis of Linguistic Structures of Gender and Gendered Authority in Shakespearean Stage Literature as a Scholarly Alternative to Conventional Generic Categories
… to quantitative language measurement, and topic modelling. In Chapter 1, I discuss three emblematic examples of technically expert scholars seeking to reconcile the apparent objectivity of quantitative, computational and mathematical research methods with the qualitative, semantic …
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"Meat of the Future": Evaluation of the sensory characteristics of cell-cultured and traditional meat products
Cell-cultured meat (CM), a meat alternative grown in vitro, is increasingly promoted as conventional meat produced more sustainably. Consumer acceptance remains a critical factor for CM's success. Thus, despite CM's limited availability consumer acceptance of CM has been widely investigated and …
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