Distributional clustering of words for text classification
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Finding out about: a cognitive perspective on search engine technology and the WWW
Finding out about: a cognitive perspective on search engine technology and the WWW
Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
Bipartite graph partitioning and data clustering
Proceedings of the tenth international conference on Information and knowledge management
Text Categorization Based on Regularized Linear Classification Methods
Information Retrieval
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
The Journal of Machine Learning Research
Editorial: Advances in Mixture Models
Computational Statistics & Data Analysis
Real-time automatic tag recommendation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A sparse gaussian processes classification framework for fast tag suggestions
Proceedings of the 17th ACM conference on Information and knowledge management
Document analysis and visualization with zero-inflated poisson
Data Mining and Knowledge Discovery
Editorial: 2nd Special issue on matrix computations and statistics
Computational Statistics & Data Analysis
An adaptive gradient BYY learning rule for poisson mixture with automated model selection
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Automatic tag recommendation algorithms for social recommender systems
ACM Transactions on the Web (TWEB)
A two-way Bayesian mixture model for clustering in metagenomics
PRIB'11 Proceedings of the 6th IAPR international conference on Pattern recognition in bioinformatics
A two-way multi-dimensional mixture model for clustering metagenomic sequences
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Initializing the EM algorithm in Gaussian mixture models with an unknown number of components
Computational Statistics & Data Analysis
Probabilistic approaches to tag recommendation in a social bookmarking network
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
Journal of Multivariate Analysis
Model based clustering of customer choice data
Computational Statistics & Data Analysis
Tag recommendation for social bookmarking: Probabilistic approaches
Multiagent and Grid Systems - Principles and Practice of Multi-Agent Systems
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An approach to simultaneous document classification and word clustering is developed using a two-way mixture model of Poisson distributions. Each document is represented by a vector with each dimension specifying the number of occurrences of a particular word in the document in question. As a collection of documents across several classes usually makes use of a large number of words, the document vectors are of high dimension. On the other hand, the number of distinct words in any single document is usually substantially smaller than the size of the vocabulary, leading to sparse document vectors. A mixture of Poisson distributions is used to model the multivariate distribution of the word counts in the documents within each class. To address the issues of high dimensionality and sparsity, the parameters in the mixture model are regularized by imposing a clustering structure on the set of words. An EM-style algorithm for the two-way mixture model will be derived for parameter estimation with the clustering of words part of the estimation process. The connection of the two-way mixture model with dimension reduction will also be elucidated. Experiments on the newsgroup data have demonstrated promising results.