A probabilistic framework for the hierarchic organisation and classification of document collections

Journal of Intelligent Information Systems

Volumn 18, Issue 2-3, 2002, Pages 153-172

  Vinokourov, Alexei ^a   Girolami, Mark ^b  

^a UNIVERSITY OF LONDON   (United Kingdom)

^b UNIVERSITY OF THE WEST OF SCOTLAND   (United Kingdom)

Author keywords

Hierarchical probabilistic clustering; Probabilistic latent semantic analysis; Support vector machines; Text categorization

Indexed keywords

INFORMATION RETRIEVAL; PROBABILISTIC LOGICS; SEMANTICS; TEXT PROCESSING; VECTORS;

DOCUMENT COLLECTIONS; SUPPORT VECTOR MACHINES;

INFORMATION MANAGEMENT;

EID: 0036498205     PISSN: 09259902     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1013677411002     Document Type: Article

References (38)

1. A hierarchical latent variable model for data visualization
2. Bayesian classification (autoclass): Theory and results
3. Bringing order to the web: Automatically categorising search results
4. Efficient approximations for the marginal likelihood of bayesian networks with hidden variables
5. A bayesian approach to learning bayesian networks with local structure
6. A bayesian method for the induction of probabilistic networks from data
7. Learning to extract symbolic knowledge from the world wide web
8. Indexing by latent semantic analysis
9. Inductive learning algorithms and representations for text categorisation
10. Hierarchical classification of web content
11. Bayesian classification with correlation and inheritance
12. Learning bayesian networks: The combination of knowledge and statistical data
13. Probabilistic latent semantic analysis
14. Learning the similarity of documents: An information-geometric approach to document retrieval and categorization
15. Maximum entropy discrimination
16. Maximum entropy discrimination
17. Exploiting generative models in discriminative classifiers
18. A probabilistic analysis of the rocchio algorithm with TFIDF for text categorization
19. Text categorization with support vector machines: Learning with many relevant features
20. An introduction to variational methods for graphical models
21. Hierarchical mixture of experts and the EM algorithm
22. A comparison of event models for naive bayes text classification
23. Learning with mixtures of trees
24. Latent semantic indexing: A probabilistic analysis
25. Score and information for recursive exponential models with incomplete data
26. Generalized model selection for unsupervised learning in high dimensions
27. Learning mixture hierarchies
28. A probabilistic hierarchical clustering method for organizing collections of text documents
29. Exploiting hierarchy in text categorisation