Abstract
Collaborative filtering has been very successful in both applications and researches. In real situation, different users may have different influences on other users’ decisions. Those authoritative users usually play more important roles. But few existing collaborative filtering algorithms consider the authorities of users. In this paper, we present the concepts of global and domain authorities of users, and apply them in collaborative filtering algorithms. This paper designs the experiments and discusses the effects of global and domain authorities. The initial results show our method can improve the performance of collaborative filtering algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Xing, Z.C.-X., Zhou, L.-Z.: Similarity Measure and Instance Selection for Collaborative Filtering. In: Proceedings of 12th International World Wide Web conference (2003)
Breese, J.S., Heckerman, D., Kadie, C.: Empirical Analysis of Predictive Algorithms for Collaborative Filtering. In: Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence, pp. 43–52 (1998)
Chien, Y.-H., George, E.I.: A Bayesian Model for Collaborative Filtering. In: Proc. Seventh Int’l Workshop Artificial Intelligence and Statistics (1999)
Hofmann, T.: Collaborative Filtering via Gaussian Probabilistic Latent Semantic Analysis. In: Proc. 26th Ann. Int’l ACM SIGIR Conf. (2003)
Hofmann, T.: Latent Semantic Models for Collaborative Filtering. ACM Trans. Information Systems 22(1), 89–115 (2004)
Sarwar, B., Karypis, G., Konstan, J., et al.: Item based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International World Wide Web Conference, pp. 285–295 (2001)
Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. In: Proceedings of the Seventh International World Wide Web Conference (1998)
Kleinberg, J.: Authoritative sources in a hyperlinked environment. In: Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (1998)
Spoerri, A.: Authority and Ranking Effects in Data Fusion. Journal of the American society for information science and technology 59(3), 450–460 (2008)
Domingos, P., Richardson, M.: Mining the Network Value of Customers. In: Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, pp. 57–66. ACM Press, New York (2001)
Rashid, A., Karypis, G., Riedl, J.: Influence in Ratings-Based Recommender Systems: An Algorithm-Independent Approach. In: SDM (2005)
MovieLens: http://movielens.umn.edu
Herlocker, J., Konstan, J., Terveen, L., Riedl, J.: Evaluating Collaborative Filtering Recommender Systems. ACM Transactions on Information Systems 22, 5–53 (2004)
Sarwar, B.M., Karypis, G., Konstan, J.A., Riedl, J.: Analysis of Recommendation Algorithms for E-Commerce. In: Proceedings of the ACM EC 2000 Conference Minneapolis, MN, pp. 158–167 (2000)
Herlocker, J., Konstan, J., Borchers, A., Riedl, J.: An Algorithmic Framework for Performing Collaborative Filtering. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 1999, pp. 230–237 (1999)
Lemire, D., Maclachlan, A.: Slope One Predictors for Online Rating-Based Collaborative Filtering. In: SIAM Data Mining (SDM 2005), Newport Beach, California, April 21-23 (2005)
Si, L., Jin, R.: Flexible mixture model for collaborative filtering. In: Proceedings of the Twentieth International Conference on Machine Learning (2003)
Bezbek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)
Pennock, D.M., Horvitz, E., Lawrence, S., Giles, C.L.: Collaborative filtering by personality diagnosis: A hybrid memory- and model-based approach. In: The Proceeding of the Sixteenth Conference on Uncertainty in Artificial Intelligence (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhou, L., Zhang, Y., Xing, CX. (2008). A Collaborative Filtering Algorithm Based on Global and Domain Authorities. In: Buchanan, G., Masoodian, M., Cunningham, S.J. (eds) Digital Libraries: Universal and Ubiquitous Access to Information. ICADL 2008. Lecture Notes in Computer Science, vol 5362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89533-6_17
Download citation
DOI: https://doi.org/10.1007/978-3-540-89533-6_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89532-9
Online ISBN: 978-3-540-89533-6
eBook Packages: Computer ScienceComputer Science (R0)