Characterizing browsing strategies in the World-Wide Web
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
How people revisit web pages: empirical findings and implications for the design of history systems
International Journal of Human-Computer Studies - Special issue: World Wide Web usability
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Web page revisitation revisited: implications of a long-term click-stream study of browser usage
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Large scale analysis of web revisitation patterns
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Tag-based user modeling for social multi-device adaptive guides
User Modeling and User-Adapted Interaction
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Large scale query log analysis of re-finding
Proceedings of the third ACM international conference on Web search and data mining
Anatomy of the long tail: ordinary people with extraordinary tastes
Proceedings of the third ACM international conference on Web search and data mining
Stochastic models for tabbed browsing
Proceedings of the 19th international conference on World wide web
A characterization of online browsing behavior
Proceedings of the 19th international conference on World wide web
Recsplorer: recommendation algorithms based on precedence mining
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Patterns of temporal variation in online media
Proceedings of the fourth ACM international conference on Web search and data mining
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
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User interest in topics and resources is known to be recurrent and to follow specific patterns, depending on the type of topic or resource. Traditional methods for predicting reoccurring patterns are based on ranking and associative models. In this paper we identify several 'canonical' patterns by clustering keywords related to visited resources, making use of a large repository of Web usage data. The keywords are derived from a 'virtual' folksonomy of tags assigned to these resources using a collaborative bookmarking system.