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 61 for “"latent Dirichlet allocation"”.
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Map-guided hyperspectral image superpixel segmentation using semi-supervised partial membership latent Dirichlet allocation
Many superpixel segmentation algorithms which are suitable for the regular color images like images with three channels: red, green and blue (RGB images) have been developed in the literature. However, because of the high dimensionality of hyperspectral imagery, these regular superpixel …
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Understanding consumer engagement with vertical farming brands on Twitter: An approach of guided Latent Dirichlet Allocation for topic modeling
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
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SELF-ENHANCED VOCABULARY LEARNING LATENT DIRECHLET ALLOCATION
… In the latter, topics models such as Latent Dirichlet Allocation (LDA) (Blei et al., 2003) and Biterm Topic Model (BTM) (Yan et al., 2013) are conventional probabilistic models designed to unveil latent topic structure within texts. In the paper, we proposed a novel topic model to …
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Automatic detection of research interest using topic modeling
… The topic model was generated using a variant of Latent Dirichlet Allocation coupled with a pointwise mutual information analysis between topic keywords and latent topics.
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Analysis of breast tissue microarray spots
… based on either multi-layer perceptrons or latent Dirichlet allocation models. A classification accuracy of 74.6 % was achieved. Tumour and normal spots were scored via an approach that involved the computation of global features formalising the quickscore values used by pathologists, and …
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New optimization approaches to matrix factorization problems with connections to natural language processing
… sensing, discrete component analysis, and latent Dirichlet allocation. For each new formulations, we develop efficient solution algorithms using discrete and robust optimization, and demonstrate tractability and effectiveness in computational experiments. In Chapter 1, we develop a …
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Topic modeling in game reviews
… 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 and interpreted these …
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An Exploration of Multimodal Document Classification Strategies
… image meta-feature vector combination and latent Dirichlet allocation-based image meta-feature extraction. Another technique that exploits correlations between text and image cleans image with text information. Experiments on real-world databases from Wikipedia demonstrate the benefits of …
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Non-parametric bayesian methods for structured topic models
… techniques (e.g., the two-parameter Poisson-Dirichlet process (PDP)) and Markov chain Monte Carlo methods. Two preliminary contributions of this thesis are 1. The Compound Poisson-Dirichlet process (CPDP): it is an extension of the PDP that can be applied to multiple input distributions. 2. …
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Non-parametric bayesian methods for structured topic models
… techniques (e.g., the two-parameter Poisson-Dirichlet process (PDP)) and Markov chain Monte Carlo methods. Two preliminary contributions of this thesis are 1. The Compound Poisson-Dirichlet process (CPDP): it is an extension of the PDP that can be applied to multiple input distributions. 2. …
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Decoding Relations between Geopolitical Risk and Financial Markets
… conflict and China-related tensions. Using Latent Dirichlet Allocation (LDA) topic modeling, it identifies key topics discussed in business media. Through ordinary least squares and quantile regression analyses, the thesis examines the relationship between topic sentiment (polarity) and hype …
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Prediction and analysis of degree of suicidal ideation in online content
… explain risk labels. Finally, we find, using a Latent Dirichlet Allocation (LDA) topic model, that users labeled at-risk for suicide post about different topics to the rest of Reddit than non-suicidal users.
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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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Hierarchical topic map generation for exploratory browsing
… finally land upon the desired document. We use Latent Dirichlet Allocation to generate the top level topics and then leverage paradigmatic and syntagmatic relations between words to construct the hierarchy. We characterize each topic in the hierarchy by a single phrase. Our topic map captures …
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Performance analysis of machine learning applications on rapid: a highly parallel computer architecture
… K-Means, K-Nearest Neighbors, Linear Regression, Latent Dirichlet Allocation, Deep Neural Network, and Radix Sort on RAPID. RAPID is a highly parallel computer architecture developed at Oracle Labs for accelerating and improving the performance of database analytic workloads. We find that the …
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Análisis de discurso en medios de comunicación digitales sobre corrupción en salud en Colombia (2022-2023), mediante técnicas de procesamiento de lenguaje natural (PLN)
… El modelado temático se implementó mediante Latent Dirichlet Allocation (LDA), complementado con enfoques alternativos para evaluar la estabilidad y consistencia de la estructura temática. Asimismo, el análisis de sentimiento se realizó mediante un modelo contextual basado en transformers, …
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Silence is Golden? Evidence from Social Disclosure Gap
… to the firms’ cost of equity capital. I employ Latent Dirichlet Allocation, an unsupervised machine leaning technique to compare the thematic content of news articles and company reports, comprising of 5 billion words to compute the social disclosure gap for a sample of 1801 US firms. I find …
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Diagnosis based specialist identification in the hospital
… baseline and that the best technique, which uses Latent Dirichlet Allocation (LDA), provides precision and recall above 80% for many diagnosis specialties based on a study with one year of chart accesses and discharge diagnoses from a major hospital. Furthermore, we explored several data mining …
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