ACM Computing Surveys (CSUR)
Mining the Web: Discovering Knowledge from HyperText Data
Mining the Web: Discovering Knowledge from HyperText Data
Integrating Web Usage and Content Mining for More Effective Personalization
EC-WEB '00 Proceedings of the First International Conference on Electronic Commerce and Web Technologies
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
The use of web structure and content to identify subjectively interesting web usage patterns
ACM Transactions on Internet Technology (TOIT)
Web unit mining: finding and classifying subgraphs of web pages
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
PageCluster: Mining conceptual link hierarchies from Web log files for adaptive Web site navigation
ACM Transactions on Internet Technology (TOIT)
Learning important models for web page blocks based on layout and content analysis
ACM SIGKDD Explorations Newsletter
AWIC'03 Proceedings of the 1st international Atlantic web intelligence conference on Advances in web intelligence
Web document clustering using hyperlink structures
Computational Statistics & Data Analysis
Searchstrings revealing user intent: a better understanding of user perception
ICWE '06 Proceedings of the 6th international conference on Web engineering
Web performance indicator by implicit user feedback – application and formal approach
WISE'05 Proceedings of the 6th international conference on Web Information Systems Engineering
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The design and organization of a website reflects the authors intent. Since user perception and understanding of websites may differ from the authors, we propose a means to identify and quantify this difference in perception. In our approach we extract perceived semantic focus by analyzing user behavior in conjunction with keyword similarity. By combining usage and content data we identify user groups with regard to the subject of the pages they visited. Our real world data shows that these user groups are nicely distinguishable by their content focus. By introducing a distance measure of keyword coincidence between web pages and user groups, we can identify pages of similar perceived interest. A discrepancy between perceived distance and link distance in the web graph indicates an inconsistency in the web site's design. Determining usage similarity allows the web site author to optimize the content to the users needs.