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Secure latent Dirichlet allocation [PDF]

open access: yesFrontiers in Digital Health
Topic 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
doaj   +9 more sources

Latent Dirichlet Allocation modeling of environmental microbiomes. [PDF]

open access: yesPLoS Computational Biology, 2023
Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given ...
Anastasiia Kim   +3 more
doaj   +4 more sources

Latent Dirichlet allocation model for world trade analysis. [PDF]

open access: yesPLoS 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
doaj   +2 more sources

A Zero-Inflated Latent Dirichlet Allocation Model for Microbiome Studies [PDF]

open access: yesFrontiers in Genetics, 2021
The human microbiome consists of a community of microbes in varying abundances and is shown to be associated with many diseases. An important first step in many microbiome studies is to identify possible distinct microbial communities in a given data set
Rebecca A. Deek, Hongzhe Li
doaj   +2 more sources

LDA filter: A Latent Dirichlet Allocation preprocess method for Weka. [PDF]

open access: yesPLoS ONE, 2020
This work presents an alternative method to represent documents based on LDA (Latent Dirichlet Allocation) and how it affects to classification algorithms, in comparison to common text representation.
P Celard   +3 more
doaj   +2 more sources

Application of Latent Dirichlet Allocation (LDA) for clustering financial tweets [PDF]

open access: yesE3S Web of Conferences, 2021
Sentiment classification is one of the hottest research areas among the Natural Language Processing (NLP) topics. While it aims to detect sentiment polarity and classification of the given opinion, requires a large number of aspect extractions.
Fatima-Zahrae Sifi   +2 more
doaj   +1 more source

Advancements of Artificial Intelligence Techniques in the Realm About Library and Information Subject—A Case Survey of Latent Dirichlet Allocation Method

open access: yesIEEE Access, 2023
To investigate the advancements of artificial intelligence techniques in the realm of library and information subject, we have chosen the Latent Dirichlet Allocation method as a case study to explore its current study status and implementations ...
Xinzhou Pan, Yu Xu
doaj   +1 more source

Applying latent Dirichlet allocation for analysis of publications in scientometric databases

open access: yesTrudy Odesskogo Politehničeskogo Universiteta, 2014
The aim of the work is to determine the most appropriate model for a thematic classification of scientific publications by author with the same sirname.
А. С. Коляда   +2 more
doaj   +5 more sources

Web content topic modeling using LDA and HTML tags [PDF]

open access: yesPeerJ Computer Science, 2023
An immense volume of digital documents exists online and offline with content that can offer useful information and insights. Utilizing topic modeling enhances the analysis and understanding of digital documents.
Hamza H.M. Altarturi   +2 more
doaj   +2 more sources

A Spectral Algorithm for Latent Dirichlet Allocation [PDF]

open access: yesAlgorithmica, 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
openaire   +6 more sources

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