Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
ACM SIGKDD Explorations Newsletter
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Exploiting hierarchical domain structure to compute similarity
ACM Transactions on Information Systems (TOIS)
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
OntoEdit: Guiding Ontology Development by Methodology and Inferencing
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Analysis of navigation behaviour in web sites integrating multiple information systems
The VLDB Journal — The International Journal on Very Large Data Bases
The use of web structure and content to identify subjectively interesting web usage patterns
ACM Transactions on Internet Technology (TOIT)
AWIC'03 Proceedings of the 1st international Atlantic web intelligence conference on Advances in web intelligence
Clustering web sessions by levels of page similarity
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Integrating web conceptual modeling and web usage mining
WebKDD'04 Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Ontology-based filtering mechanisms for web usage patterns retrieval
EC-Web'05 Proceedings of the 6th international conference on E-Commerce and Web Technologies
Representation and dimensionality reduction of semantically enriched clickstreams
Ph.D. '08 Proceedings of the 2008 EDBT Ph.D. workshop
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Web Usage Mining (WUM) is the application of data mining techniques over web server logs in order to extract navigation usage patterns. Identifying the relevant and interesting patterns, and to understand what knowledge they represent in the domain is the goal of the Pattern Analysis phase, one of the phases of the WUM process. Pattern analysis is a critical phase in WUM due to two main reasons: a) mining algorithms yield a huge number of patterns; b) there is a significant semantic gap between URLs and events performed by users. In this paper, we discuss an ontology-based approach to support the analysis of sequential navigation patterns, discussing the main features of the O3R (Ontology-based Rules Retrieval and Rummaging) prototype. O3R functionality is targeted at supporting the comprehension of patterns through interactive pattern rummaging, as well as on the identification of potentially interesting ones. All functionality is based on the availability of the domain ontology, which dynamically provides meaning to URLs. The paper provides an overall view of O3R, details the rummaging functionality, and discusses preliminary results on the use of O3R.