Results 21 to 30 of about 63,472 (294)

Latent dirichlet markov allocation for sentiment analysis [PDF]

, 2013
In recent years probabilistic topic models have gained tremendous attention in data mining and natural language processing research areas. In the field of information retrieval for text mining, a variety of probabilistic topic models have been used to ...
Bagheri, A, de Jong, F, Saraee, MH
core   +7 more sources

An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation. [PDF]

Brief Bioinform, 2023
Yang Q, Xu Z, Zhou W, Wang P, Jiang Q, Juan L.   +5 more
europepmc   +3 more sources

Gaussian hierarchical latent Dirichlet allocation: Bringing polysemy back. [PDF]

PLoS One, 2023
Topic models are widely used to discover the latent representation of a set of documents. The two canonical models are latent Dirichlet allocation, and Gaussian latent Dirichlet allocation, where the former uses multinomial distributions over words, and the latter uses multivariate Gaussian distributions over pre-trained word embedding vectors as the ...
Yoshida T, Hisano R, Ohnishi T.
europepmc   +4 more sources

Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation

Tourism Management, 2017
Stuart J Barnes
exaly   +2 more sources

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, Wafae Sabbar, Amal El Mzabi   +2 more
doaj   +1 more source

Investigating Reddit Data on Type 2 Diabetes Management During the COVID-19 Pandemic Using Latent Dirichlet Allocation Topic Modeling and Valence Aware Dictionary for Sentiment Reasoning Analysis: Content Analysis. [PDF]

JMIR Form Res
Nagpal M, Jalali N, Sherifali D, Morita P, Cafazzo JA.   +4 more
europepmc   +2 more sources

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, Muntadher Saadoon, Nor Badrul Anuar   +2 more
doaj   +2 more sources

Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey [PDF]

Multimedia tools and applications, 2017
Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data and text documents.
Hamed Jelodar, Yongli Wang, Chi Yuan, Xia Feng   +3 more
semanticscholar   +1 more source

Exploring Blockchain Research in Supply Chain Management: A Latent Dirichlet Allocation-Driven Systematic Review

Inf., 2023
Blockchain technology has emerged as a tool with the potential to enhance transparency, trust, security, and decentralization in supply chain management (SCM).
Abderahman Rejeb, Karim Rejeb, Steve Simske, John G. Keogh   +3 more
semanticscholar   +1 more source

Integrating Information Entropy and Latent Dirichlet Allocation Models for Analysis of Safety Accidents in the Construction Industry

Buildings, 2023
Construction accident investigation reports contain critical information, but extracting useful insights from the voluminous Chinese text is challenging.
Yipeng Liu, Junwu Wang, Shanrong Tang, Jiaji Zhang, Jinyingjun Wan   +4 more
semanticscholar   +1 more source