Information filtering based on user behavior analysis and best match text retrieval
SIGIR '94 Proceedings of the 17th 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
Communications of the ACM
Fab: content-based, collaborative recommendation
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
The quest for correct information on the Web: hyper search engines
Selected papers from the sixth international conference on World Wide Web
Collaborative value filtering on the Web
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Towards adaptive Web sites: conceptual framework and case study
WWW '99 Proceedings of the eighth international conference on World Wide Web
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
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A good ranking is critical to gain a positive searching experience. With usage data collected from past searching activities, it could be improved from current approaches which are largely based on text or link information. In this paper, we proposed a usage-based ranking algorithm. Basically, it calculates the rank score on time duration considering the propagated effect, which is an improvement on the simple selection frequency determined method. Besides, it also has some heuristics to further improve the accuracy of top-positioned results.