Practical prefetching via data compression
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Continual computation policies for utility-directed prefetching
Proceedings of the seventh international conference on Information and knowledge management
Using path profiles to predict HTTP requests
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Patterns of search: analyzing and modeling Web query refinement
UM '99 Proceedings of the seventh international conference on User modeling
Predicting users' requests on the WWW
UM '99 Proceedings of the seventh international conference on User modeling
Automatic Speech Recognition: The Development of the Sphinx Recognition System
Automatic Speech Recognition: The Development of the Sphinx Recognition System
Exploring Versus Exploiting when Learning User Models for Text Recommendation
User Modeling and User-Adapted Interaction
Pre-sending Documents on the WWW: A Comparative Study
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Predicting file system actions from prior events
ATEC '96 Proceedings of the 1996 annual conference on USENIX Annual Technical Conference
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Predicting category accesses for a user in a structured information space
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Cut-and-Pick Transactions for Proxy Log Mining
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Mining Web Logs to Improve Web Caching and Prefetching
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
Mining High-Quality Cases for Hypertext Prediction and Prefetching
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
A Keyword-Based Semantic Prefetching Approach in Internet News Services
IEEE Transactions on Knowledge and Data Engineering
Building Association-Rule Based Sequential Classifiers for Web-Document Prediction
Data Mining and Knowledge Discovery
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
Predicting query reformulation during web searching
CHI '09 Extended Abstracts on Human Factors in Computing Systems
An MDP-based recommender system
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Web access path prediction using fuzzy case based reasoning
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Modeling cellular user mobility using a leap graph
PAM'13 Proceedings of the 14th international conference on Passive and Active Measurement
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The rapid development of Internet has resulted in more and more multimedia in Web content. However, due to the limitation in the bandwidth and huge size of the multimedia data, users always suffer from long time waiting. On the other hand, if we can predict the web object or page that the user most likely will view next while the user is viewing the current page, and pre-fetch the content, then the perceived network latency can be significantly reduced. In this paper, we present an n-gram based model to utilize path profiles of users from very large web log to predict the users' future requests. Our model is based on a simple extension of existing point-based models for such predictions, but our results show that by sacrificing the applicability somewhat one can gain a great deal in prediction precision. Also we present an efficient method to compress the prediction model size so that it can be fitted into the main memory. Our result can potentially be applied to a wide range of applications on the web, including pro-fetching, enhancement of recommendation systems as well as web caching policies. The experiments based on three realistic web logs have proved the effectiveness of the proposed scheme.