Journal article
Webmining: Learning from the World Wide Web
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.
Language: | English |
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Year: | 2002 |
Pages: | 517-532 |
ISSN: | 18727352 and 01679473 |
Types: | Journal article |
DOI: | 10.1016/S0167-9473(01)00076-7 |
ORCIDs: | Larsen, Jan and Hansen, Lars Kai |