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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Petridou, S.G. Koutsonikola, V.A. Vakali, A.I. Papadimitriou, G.I. |
| Copyright Year | 1989 |
| Abstract | Web users' clustering is a crucial task for mining information related to users' needs and preferences. Up to now, popular clustering approaches build clusters based on usage patterns derived from users' page preferences. This paper emphasizes the need to discover similarities in users' accessing behavior with respect to the time locality of their navigational acts. In this context, we present two time-aware clustering approaches for tuning and binding the page and time visiting criteria. The two tracks of the proposed algorithms define clusters with users that show similar visiting behavior at the same time period, by varying the priority given to page or time visiting. The proposed algorithms are evaluated using both synthetic and real data sets and the experimentation has shown that the new clustering schemes result in enriched clusters compared to those created by the conventional non-time-aware user clustering approaches. These clusters contain users exhibiting similar access behavior in terms not only of their page preferences but also of their access time. |
| Sponsorship | IEEE IEEE Comput. Soc. Tech. Committee on Data Eng IEEE Computer Society |
| Starting Page | 653 |
| Ending Page | 667 |
| Page Count | 15 |
| File Size | 1414589 |
| File Format | |
| ISSN | 10414347 |
| Volume Number | 20 |
| Issue Number | 5 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Navigation Clustering algorithms Context awareness Prefetching Web server Informatics Partitioning algorithms Performance evaluation Pattern analysis access time Web mining Web users clustering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Information Systems Computational Theory and Mathematics Computer Science Applications |
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