TITLE: Webmining: Learning from the World Wide Web
AUTHORS: J. Larsen, L.K. Hansen, A. Szymkowiak, T. Christiansen and T. Kolenda
Informatics and Mathematical Modelling, Building 321
Technical University of Denmark, DK-2800 Lyngby, Denmark
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
The modeling is based on independent component analysis and hierarchical
probabilistic clustering techniques.
Appears in special issue of Computational Statistics and Data Analysis, 2001.