Abstract
This paper presents a document recommendation system based on clustering peer-to-peer networks. It’s an unstructured P2P system. In this system each agent-peer can learn user’s interest, then it helps user share and recommend documents with the other users. Since each peer in our P2P networks is a node, in order to cluster them, we import the concept of Group. Each group is composed of peers. The types of documents, which belong to a same group, are uniform. This paper presents how these peers help users to share and to recommend documents, and how they cluster into groups. Our experiment results show the advantages of the document recommendation system.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Plonka, D.: Napster traffic measurement. Technical report, University of Wisconsin-Madison (2000)
Funakoshi, K., Ohguro, T.: A content-based collaborative recommender system with detailed use of evaluations. In: Fourth International Conference on knowledge-Based In-telligent Engineering Systems & Allied Technologies, pp. 253–256 (2000)
Kamahara, J., Asakawa, T.: A Community-based Recommendation System to Reveal Unexpected Interests. In: Proceedings of the 11th International Mutmedia Modeling Conference, pp. 433–438 (2005)
Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Analysis of Recommendation Algorithms for E-Commerce. In: Proceedings of the ACM EC 2000 Conference, pp. 158–167 (2000)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: An Open Architecture for Collaborative Filtering of Netnews. In: Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, October 22-26, 1994, pp. 175–186 (1994)
Zhang, T., Ramakrishnan, R., Livny, M.: BIRCH: An Efficient Data Clustering Method for Very Large Databases. In: Proceedings of the 1996 ACM SIGMOD international conference, ACM Press, New York (1996)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Guo, F., Li, S. (2007). A Document Recommendation System Based on Clustering P2P Networks. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2007. Lecture Notes in Computer Science, vol 4674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74780-2_27
Download citation
DOI: https://doi.org/10.1007/978-3-540-74780-2_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74779-6
Online ISBN: 978-3-540-74780-2
eBook Packages: Computer ScienceComputer Science (R0)