Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
From user access patterns to dynamic hypertext linking
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
Learning human-like knowledge by singular value decomposition: a progress report
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
INsite: introduction to a generic paradigm for interpreting user-Web space interaction
Proceedings of the 2nd international workshop on Web information and data management
Proceedings of the 1998 conference on Advances in neural information processing systems II
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Exploiting Hierarchy in Text Categorization
Information Retrieval
Creating Adaptive Web Sites Through Usage-Based Clustering of URLs
KDEX '99 Proceedings of the 1999 Workshop on Knowledge and Data Engineering Exchange
Knowledge discovery from users Web-page navigation
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Modeling text with generalizable Gaussian mixtures
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal implementations of UPGMA and other common clustering algorithms
Information Processing Letters
Graph theory application and web page ranking for website link structure improvement
Behaviour & Information Technology
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Automated analysis of the world wide web is a new challenging area relevant in many applications, e.g., retrieval, navigation and organization of information, automated information assistants, and e-commerce. This paper discusses the use of unsupervised and supervised learning methods for user behavior modeling and content-based segmentation and classification of web pages. The modeling is based on independent component analysis and hierarchical probabilistic clustering techniques.