The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Effective personalization based on association rule discovery from web usage data
Proceedings of the 3rd international workshop on Web information and data management
An Intelligent Web Recommendation System: A Web Usage Mining Approach
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Mining Access Patterns Efficiently from Web Logs
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Position coded pre-order linked WAP-tree for web log sequential pattern mining
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Replaying live-user interactions in the off-line evaluation of critique-based mobile recommendations
Proceedings of the 2007 ACM conference on Recommender systems
Efficient mining top-k regular-frequent itemset using compressed tidsets
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Contemporary Issues in Handheld Computing Research
International Journal of Handheld Computing Research
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As mobile phones continue to infiltrate the world, they could easily become the Internet client of choice—especially considering widespread adoption of third-generation mobile services. Although the mobile phone's disproportionately small screen is ill-suited for Web surfing, it's here to stay because it's constrained by portability requirements. Using recommendations can aid mobile Web surfing. Unlike most Web recommendation approaches that use clustering and association rule mining, this approach identifies frequent sequential Web-access patterns. A tree structure called pattern-tree stores the patterns and then generates recommended links. Experimental evaluations of the approach illustrate its effectiveness.This article is part of a special issue on AI, Agents, and the Web.