Results 1 to 10 of about 63,406 (137)
Latent Dirichlet Allocation modeling of environmental microbiomes. [PDF]
PLoS Comput Biol, 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 ...
Kim A, Sevanto S, Moore ER, Lubbers N.
europepmc +4 more sources
Latent Dirichlet allocation model for world trade analysis. [PDF]
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.
Kozlowski D, Semeshenko V, Molinari A.
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A Zero-Inflated Latent Dirichlet Allocation Model for Microbiome Studies. [PDF]
Front Genet, 2020 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
Deek RA, Li H.
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Topic Modelling of Swedish Newspaper Articles about Coronavirus: a Case Study using Latent Dirichlet Allocation Method [PDF]
arXiv, 2023 Topic Modelling (TM) is from the research branches of natural language understanding (NLU) and natural language processing (NLP) that is to facilitate insightful analysis from large documents and datasets, such as a summarisation of main topics and the topic changes.
Griciūtė B, Han L, Nenadic G.
europepmc +1 more source
Latent Dirichlet Allocation in predicting clinical trial terminations. [PDF]
BMC Med Inform Decis Mak, 2019 Background This study used natural language processing (NLP) and machine learning (ML) techniques to identify reliable patterns from within research narrative documents to distinguish studies that complete successfully, from the ones that terminate ...
Geletta S, Follett L, Laugerman M.
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LDA filter: A Latent Dirichlet Allocation preprocess method for Weka. [PDF]
PLoS 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.
Celard P +3 more
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Application of Latent Dirichlet Allocation (LDA) for clustering financial tweets [PDF]
E3S 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
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IEEE 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
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Web content topic modeling using LDA and HTML tags [PDF]
PeerJ 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
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Acta Universitatis Sapientiae: Economics and Business, 2022 This article develops a baseline on how to analyse the statements of monetary policy from Lesotho’s Central Bank using a method of topic classification that utilizes a machine learning algorithm known as Latent Dirichlet Allocation.
Damane Moeti
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