The latent topic block model for the co-clustering of textual interaction data

DOI10.1016/j.csda.2019.03.005OpenAlexW2890327461MaRDI QIDQ2416785

Marco Corneli, Charles Bouveyron, Pierre Latouche, Laurent R. Bergé

Publication date: 24 May 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2019.03.005

zbMATH Keywords

variational inferenceco-clusteringtopic modellatent block modeltext matrices

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (4)

Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance ⋮ A survey on model-based co-clustering: high dimension and estimation challenges ⋮ Embedded topics in the stochastic block model ⋮ Greedy clustering of count data through a mixture of multinomial PCA

Uses Software

• JGibbLDA

Cites Work

• Unnamed Item
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• Latent Block Model for Contingency Table
• The stochastic topic block model for the clustering of vertices in networks with textual edges
• Block clustering with collapsed latent block models
• Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
• Block clustering with Bernoulli mixture models: comparison of different approaches
• Another interpretation of the EM algorithm for mixture distributions
• Estimating the dimension of a model
• Text classification from labeled and unlabeled documents using EM
• Model-based co-clustering for ordinal data
• 10.1162/jmlr.2003.3.4-5.993
• Estimation and selection for the latent block model on categorical data

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