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Secure latent Dirichlet allocation
Frontiers in Digital HealthTopic modelling refers to a popular set of techniques used to discover hidden topics that occur in a collection of documents. These topics can, for example, be used to categorize documents or label text for further processing. One popular topic modelling
Thijs Veugen +4 more
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Collective Latent Dirichlet Allocation
2008 Eighth IEEE International Conference on Data Mining, 2008 In this paper, we propose a new variant of latent Dirichlet allocation (LDA): Collective LDA (C-LDA), for multiple corpora modeling. C-LDA combines multiple corpora during learning such that it can transfer knowledge from one corpus to another; meanwhile it keeps a discriminative node which represents the corpus ID to constrain the learned topics in ...
Zhiyong Shen, Jun Sun, Yi-Dong Shen
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Text Categorization with Latent Dirichlet Allocation [PDF]
Journal of Electrical and Electronics Engineering, 2014 This paper focuses on the text categorization of Slovak text corpora using latent Dirichlet allocation. Our goal is to build text subcorpora that contain similar text documents.
ZLACKÝ Daniel +3 more
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Automatic topic detection strategy for information retrieval in spoken document [PDF]
, 2009 This paper suggests an alternative solution for the task of spoken document retrieval (SDR). The proposed system runs retrieval on multi-level transcriptions (word and phone) produced by word and phone recognizers respectively, and their outputs are ...
Misra, H. +3 more
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High performance latent dirichlet allocation for text mining [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Latent Dirichlet Allocation (LDA), a total probability generative model, is a three-tier Bayesian model. LDA computes the latent topic structure of the data
Liu, Zelong
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Similarity Measures Based on Latent Dirichlet Allocation
, 2013 We present in this paper the results of our investigation on semantic similarity measures at word- and sentence-level based on two fully-automated approaches to deriving meaning from large corpora: Latent Dirichlet Allocation, a probabilistic approach, and Latent Semantic Analysis, an algebraic approach.
Vasile Rus +2 more
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A Spectral Algorithm for Latent Dirichlet Allocation [PDF]
Algorithmica, 2014 The problem of topic modeling can be seen as a generalization of the clustering problem, in that it posits that observations are generated due to multiple latent factors (e.g., the words in each document are generated as a mixture of several active topics, as opposed to just one).
Anima Anandkumar +4 more
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Ranking social bookmarks using topic models [PDF]
, 2010 Ranking of resources in social tagging systems is a difficult problem due to the inherent sparsity of the data and the vo- cabulary problems introduced by having a completely unre- stricted lexicon.
Carman, Mark J. +8 more
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Latent Dirichlet allocation model for world trade analysis.
PLoS ONE, 2021 International trade is one of the classic areas of study in economics. Its empirical analysis is a complex problem, given the amount of products, countries and years.
Diego Kozlowski +2 more
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Inference in Supervised latent Dirichlet allocation [PDF]
2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011 Supervised latent Dirichlet allocation (Supervised-LDA) [1] is a probabilistic topic model that can be used for classification. One of the advantages of Supervised-LDA over unsupervised LDA is that it can potentially learn topics that are inline with the class label.
Balaji Lakshminarayanan, Raviv Raich
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