Abstract
In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optimal amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group.
Originalsprog | Engelsk |
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Titel | Proceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond |
Forlag | University of Kassel |
Publikationsdato | okt. 2010 |
Sider | 315-321 |
Kapitel | 6 |
Status | Udgivet - okt. 2010 |
Begivenhed | LWA 2010 - Kassel, Tyskland Varighed: 4 okt. 2010 → 6 okt. 2010 |
Konference
Konference | LWA 2010 |
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Land/Område | Tyskland |
By | Kassel |
Periode | 04/10/2010 → 06/10/2010 |