Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
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
Predicting users' requests on the WWW
UM '99 Proceedings of the seventh international conference on User modeling
Mining navigation history for recommendation
Proceedings of the 5th international conference on Intelligent user interfaces
Automatic personalization based on Web usage mining
Communications of the ACM
What do web users do? An empirical analysis of web use
International Journal of Human-Computer Studies
Mining sequential patterns with constraints in large databases
Proceedings of the eleventh international conference on Information and knowledge management
Measuring Search Engine Quality
Information Retrieval
User Modeling and User-Adapted Interaction
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Mining Generalized Association Rules for Sequential and Path Data
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Evaluation of web usage mining approaches for user's next request prediction
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
Selective Markov models for predicting Web page accesses
ACM Transactions on Internet Technology (TOIT)
FS-Miner: efficient and incremental mining of frequent sequence patterns in web logs
Proceedings of the 6th annual ACM international workshop on Web information and data management
Predictive Algorithms for Browser Support of Habitual User Activities on the Web
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
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
Robustness of collaborative recommendation based on association rule mining
Proceedings of the 2007 ACM conference on Recommender systems
Predicting WWW surfing using multiple evidence combination
The VLDB Journal — The International Journal on Very Large Data Bases
Large scale analysis of web revisitation patterns
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A Markov Prediction Model Based on Page Hierarchical Clustering
International Journal of Distributed Sensor Networks
Pre-sending documents on the WWW: a comparative study
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Mining Indirect Association Rules for Web Recommendation
International Journal of Applied Mathematics and Computer Science
Recsplorer: recommendation algorithms based on precedence mining
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
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Users of collaborative applications as well as individual users in their private environment return to previously visited Web pages for various reasons; apart from pages visited due to backtracking, they typically have a number of favorite or important pages that they monitor or tasks that reoccur on an infrequent basis. In this paper, we introduce a library of methods that facilitate revisitation through the effective prediction of the next page request. It is based on a generic framework that inherently incorporates contextual information, handling uniformly both server- and the client-side applications. Unlike other existing approaches, the methods it encompasses are real-time, since they do not rely on training data or machine learning algorithms. We evaluate them over two large, real-world datasets, with the outcomes suggesting a significant improvement over methods typically used in this context. We have also made our implementation and data publicly available, thus encouraging other researchers to use it as a benchmark and to extend it with new techniques for supporting user's navigational activity.