Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
From user access patterns to dynamic hypertext linking
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
Silk from a sow's ear: extracting usable structures from the Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Life, death, and lawfulness on the electronic frontier
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Predicting users' requests on the WWW
UM '99 Proceedings of the seventh international conference on User modeling
A prediction system for multimedia pre-fetching in Internet
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Using information scent to model user information needs and actions and the Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Modeling user interest shift using a Bayesian approach
Journal of the American Society for Information Science and Technology
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Mining longest repeating subsequences to predict world wide web surfing
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Categorizing information objects from user access patterns
Proceedings of the eleventh international conference on Information and knowledge management
A clickstream-based collaborative filtering personalization model: towards a better performance
Proceedings of the 6th annual ACM international workshop on Web information and data management
Mining interesting knowledge from weblogs: a survey
Data & Knowledge Engineering
Mining web navigations for intelligence
Decision Support Systems - Special issue: Intelligence and security informatics
Adaptive information retrieval system applied to digital libraries
WebMedia '06 Proceedings of the 12th Brazilian Symposium on Multimedia and the web
Integrating recommendation models for improved web page prediction accuracy
ACSC '08 Proceedings of the thirty-first Australasian conference on Computer science - Volume 74
Information Processing and Management: an International Journal
Mining web navigations for intelligence
Decision Support Systems - Special issue: Intelligence and security informatics
A web page usage prediction scheme using sequence indexing and clustering techniques
Data & Knowledge Engineering
A web-page usage prediction scheme using weighted suffix trees
SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
An integrated model for next page access prediction
International Journal of Knowledge and Web Intelligence
Custom ordering on digital library information retrieval
WebMedia '09 Proceedings of the XV Brazilian Symposium on Multimedia and the Web
A survey of major challenges and future directions for next generation pervasive computing
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
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In a categorized information space, predicting users' information needs at the category level can facilitate personalization, caching and other topic-oriented services. This paper presents a two-phase model to predict the category of a user's next access based on previous accesses. Phase 1 generates a snapshot of a user's preferences among categories based on a temporal and frequency analysis of the user's access history. Phase 2 uses the computed preferences to make predictions at different category granularities. Several alternatives for each phase are evaluated, using the rating behaviors of on-line raters as the form of access considered. The results show that a method based on re-access pattern and frequency analysis of a user's whole history has the best prediction quality, even over a path-based method (Markov model) that uses the combined history of all users.