Explanation-based learning: a survey of programs and perspectives
ACM Computing Surveys (CSUR)
The role of domain knowledge in data mining
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Silk from a sow's ear: extracting usable structures from the Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Effective personalization based on association rule discovery from web usage data
Proceedings of the 3rd international workshop on Web information and data management
Data Mining for Measuring and Improving the Success of Web Sites
Data Mining and Knowledge Discovery
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Dynamic Taxonomies: A Model for Large Information Bases
IEEE Transactions on Knowledge and Data Engineering
Conceptual Knowledge Discovery and Data Analysis
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Modelling and Incorporating Background Knowledge in the Web Mining Process
Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery
Intelligent web traffic mining and analysis
Journal of Network and Computer Applications - Special issue on computational intelligence on the internet
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Unix systems monitoring with FCA
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
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Web usage mining aims at the discovery of interesting usage patterns from Web server log files. "Interestingness" relates to the business goals of the site owner. However, business goals refer to business objects rather than the page hits and script invocations recorded by the site server. Hence, Web usage analysis requires a preparatory mechanism that incorporates the business goals, the concepts reflecting them and the expert's background knowledge on them into the mining process. To this purpose, we present a methodology and a mechanism for the establishment and exploitation of application-oriented concept hierarchies in Web usage analysis. We demonstrate our approach on a real data set and show how it can substantially improve both the search for interesting patterns by the mining algorithm and the interpretation of the mining results by the analyst.