Abstract
In this paper, we describe a prototype system, called PASS (Personalized Active Service System), which provides personalized services for digital libraries. User profiles are represented as probabilistic distributions of interests over different domains. The system realizes content-based filtering by computing the similarity of probabilistic distributions between documents and user profiles. In addition the system realizes collaborative filtering by clustering similar user profiles. Experimental results show its performance satisfactory.
Supported by the National Natural Science Foundation of China under Grant No. 60221120146; the National Grand Fundamental Research 973 Program of China under Grant No.G1999032704
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References
Mobasher, B., Colley, R., and Srivastava, J. Automatic personalization based on Web usage mining. Communications of the ACM, Aug. 2000, 43(8), 142–152.
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© 2002 Springer-Verlag Berlin Heidelberg
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Zeng, C., Zheng, X., Xing, C., Zhou, L. (2002). Personalized Services for Digital Library. In: Lim, E.P., et al. Digital Libraries: People, Knowledge, and Technology. ICADL 2002. Lecture Notes in Computer Science, vol 2555. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36227-4_25
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DOI: https://doi.org/10.1007/3-540-36227-4_25
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