Results 111 to 120 of about 1,075,906 (163)

Review of Latent Dirichlet Allocation Methods Usable in Voice of Customer Analysis

, 2018
The aim of the article is to detect and review existing topic modelling methods of Latent Dirichlet Allocation and their modifications usable in Voice of Customer analysis.
Lucie Sperkova
core   +1 more source

Classification of Twitter Trending Issues Through Three Clustering Methods

Jurnal Nasional Teknik Elektro
Twitter is one of the most dynamic social media platforms that provides real-time information through its trending topics feature, which reflects the most talked about issues among users.
Dwie Putri Donnaro, Dadang Gunawan
doaj   +1 more source

Topic Modeling Approach on Twitter Data Relevant to Political Changes During the COVID-19 Pandemic

Journal of Information Science Theory and Practice
The COVID-19 pandemic has affected various sectors of society, including politics. The political changes have had both positive and negative impacts on people’s lives. Different public discussions happened during that situation on social media.
M. G. D. S. Hansika, K. S. Ranasinghe, R. A. H. M. Rupasingha   +2 more
doaj   +1 more source

The sensitivity of latent dirichlet allocation for information retrieval

, 2009
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD)It has been shown that the use of topic models for Information retrieval provides an increase in precision when used in the appropriate form.
Ramamohanarao, K, Park, LAF
core   +1 more source

Latent dirichlet allocation

, 2003
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture ...
John Lafferty, David M. Blei, Michael I. Jordan, Andrew Y. Ng   +3 more
core   +1 more source

Explorando Temas en Recursos Educativos Abiertos de Tecnologías de la Información a través del Algoritmo LDA

Latin-American Journal of Computing
Este artículo aplica el algoritmo Latent Dirichlet Allocation, LDA, como una técnica de aprendizaje de máquina y minería de texto para descubrir temas en OER en el contexto de la educación en ingeniería.
Veronica Segarra-Faggioni, Audrey Romero-Pelaez, Juan Carlos Morocho-Yunga, René Ludeña   +3 more
doaj  

Ecological modelling: A computational analysis of air pollution discourses in English print media of India and Pakistan.

PLoS ONE
The present study investigates air pollution dynamics through newspaper discourse in India and Pakistan, where both countries rank among the top five countries affected by air pollution.
Sana Rabbani, Fasih Ahmed
doaj   +1 more source

A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation

, 2008
Latent Dirichlet allocation (LDA) is a Bayesian network that has recently gained much popularity in applications ranging from document modeling to computer vision.
Yee Whye Teh, David Newman, Max Welling
core  

Vectorized Bayesian Inference for Latent Dirichlet-Tree Allocation: Theory, Computation and Applications [PDF]

Latent Dirichlet Allocation (LDA) is a foundational model for discovering latent thematic structure in discrete data, but its Dirichlet prior cannot represent the rich correlations and hierarchical relationships often present among topics.
Wang, Zheng
core  

Semantic Annotation of Satellite Images using Latent Dirichlet Allocation

, 2010
We a use a semantic learning model to affect user oriented names to satellite image regions. After a supervised classification method of training subsets, we proceed to an automatic labeling by use of a Latent Dirichlet Allocation method (LDA) which does
Lienou, M., Maître, Henri, Datcu, M.
core   +1 more source