Paper:
Partially Exclusive Item Partition in MMMs-Induced Fuzzy Co-Clustering and its Effects in Collaborative Filtering
Katsuhiro Honda*, Takaya Nakano*, Chi-Hyon Oh**, Seiki Ubukata*, and Akira Notsu*
*Graduate School of Engineering, Osaka Prefecture University
1-1 Gakuen-cho, Nakaku, Sakai, Osaka 599-8531, Japan
**Faculty of Liberal Arts and Sciences, Osaka University of Economics and Law
6-10 Gakuonji, Yao, Osaka 581-8511 Japan
- [1] E. Oja, A. Ilin, J. Luttinen, and Z. Yang, “Linear expansions with nonlinear cost functions: modeling, representation, and partitioning,” 2010 IEEE World Congress on Computational Intelligence, Plenary and Invited Lectures, pp.105-123, 2010.
- [2] Z. Yang and E. Oja, “Linear and nonlinear projective nonnegative matrix factorization,” IEEE Trans. on Neural Networks, Vol.21, No.5, pp. 734-749, 2010.
- [3] K. Honda, A. Notsu, and H. Ichihashi, “Collaborative filtering by sequential user-item co-cluster extraction from rectangular relational Data,” Int. J. of Knowledge Engineering and Soft Data Paradigms, Vol.2, No.4, pp. 312-327, 2010.
- [4] L. Rigouste, O. Cappée, and F. Yvon, “Inference and evaluation of the multinomial mixture model for text clustering,” Information Processing and Management, Vol.43, No.5, pp. 1260-1280, 2007.
- [5] C.-H. Oh, K. Honda, and H. Ichihashi, “Fuzzy clustering for categorical multivariate data,” Proc. of Joint 9th IFSA World Congress and 20th NAFIPS Int. Conf., pp. 2154-2159, 2001.
- [6] K. Honda, S. Oshio, and A. Notsu, “FCM-type fuzzy co-clustering by K-L information regularization,” Proc. of 2014 IEEE Int. Conf. on Fuzzy Systems, pp. 2505-2510, 2014.
- [7] K. Honda, S. Oshio, and A. Notsu, “Fuzzy co-clustering induced by multinomial mixture models,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.19, No.6, pp. 717-726, 2015.
- [8] J. C. Bezdek, “Pattern Recognition with Fuzzy Objective Function Algorithms,” Plenum Press, 1981.
- [9] K. Honda, C.-H. Oh, and A. Notsu, “Exclusive condition on item partition in fuzzy co-clustering based on K-L information regularization,” Proc. Joint 7th Int. Conf. on Soft Computing and Intelligent Systems and 15th Int. Symp. on Advanced Intelligent Systems, pp. 1413-1417, 2014.
- [10] K. Tsuda, M. Minoh, and K. Ikeda, “Extracting straight lines by sequential fuzzy clustering,” Pattern Recognition Letters, Vol.17, pp. 643-649, 1996.
- [11] K. Honda, C.-H. Oh, Y. Matsumoto, A. Notsu, and H. Ichihashi, “Exclusive partition in FCM-type co-clustering and its application to collaborative filtering,” Int. J. of Computer Science and Network Security, Vol.12, No.12, pp. 52-58, 2012.
- [12] R. J. Hathaway, “Another interpretation of the EM algorithm for mixture distributions,” Statistics & Probability Letters, Vol.4, pp. 53-56, 1986.
- [13] K. Honda and H. Ichihashi, “Regularized linear fuzzy clustering and probabilistic PCA mixture models,” IEEE Trans. on Fuzzy Systems, Vol.13, No.4, pp. 508-516, 2005.
- [14] K. Honda, A. Notsu, and H. Ichihashi, “Fuzzy PCA-guided robust k-means clustering,” IEEE Trans. on Fuzzy Systems, Vol.18, No.1, pp. 67-79, 2010.
- [15] G. Salton and C. Buckley, “Term-weighting approaches in automatic text retrieval,” Information Processing and Management, Vol.24, Iss.5, pp. 513-523, 1988.
- [16] J. A. Konstan, B. N. Miller, D. Maltz, J. L. Herlocker, L. R. Gardon, and J. Riedl, “Grouplens: applying collaborative filtering to usenet news,” Communications of the ACM, Vol.40, No.3, pp. 77-87, 1997.
- [17] J. A. Swets, “Measuring the accuracy of diagnostic systems,” Science, Vol.240, No.4857, pp. 1285-1289, 1988.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.