Webmining: Learning from the world wide web

Computational Statistics and Data Analysis

Volumn 38, Issue 4, 2002, Pages 517-532

  Larsen, Jan ^a   Hansen, Lars Kai ^a   Have, Anna Szymkowiak ^a   Christiansen, Torben ^a   Kolenda, Thomas ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

Hierarchical probalistic clustering; Unsupervised learning; Webmining

Indexed keywords

COMPONENTS; COMPUTATIONAL METHODS; NAVIGATION;

AUTOMATED INFORMATION ASSISTANTS;

WORLD WIDE WEB;

WORLD WIDE WEB;

EID: 0037186654     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(01)00076-7     Document Type: Article

References (29)

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2. Novelty detection and neural network validation
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5. Maximum likelihood from incomplete data via the EM algorithm
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7. Unsupervised learning and generalization
8. Modeling text with generalizable Gaussian mixtures
9. Discriminant analysis by Gaussian mixtures
10. Learning human-like knowledge by singular value decomposition: A progress report
11. Probabilistic hierarchical clustering with labeled and unlabeled data
12. The automatic creation of literature abstracts
13. Creating adaptive web sites through usage-based clustering of URLs
14. Choosing an appropriate model for novelty detection
15. Text classification from labeled and unlabeled documents using EM
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17. The infinite Gaussian mixture model
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19. A data miner analyzing the navigational behaviour of web users
20. Learning mixture hierarchies
21. Exploiting hierarchy in text categorization
22. A MCMC approach to hierarchical mixture modelling
23. From user access patterns to dynamic hypertext linking