Abstract
Fuzzy co-clustering achieves dual partition of object-item pairs by estimating fuzzy memberships of them. In the multinomial mixtures-induced model, object memberships present the exclusive assignment to clusters while item memberships describe relative typicality in each cluster. In order to improve the interpretability of item partition, exclusive penalty was adopted for item memberships in previous works, where item fuzzy memberships are estimated reflecting both fuzzification penalty and exclusive penalty. In this paper, the characteristics of exclusive item penalty are further studied considering the influences of the item fuzziness weight with different fuzziness degrees.
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References
Oh, C.-H., Honda, K., Ichihashi, H.: Fuzzy clustering for categorical multivariate data. In: Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, pp. 2154–2159 (2001)
Kummamuru, K., Dhawale, A., Krishnapuram, R.: Fuzzy co-clustering of documents and keywords. In: Proceedings of the 2003 IEEE International Conference on Fuzzy Systems, vol. 2, pp. 772–777 (2003)
Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)
Miyamoto, S., Ichihashi, H., Honda, K.: Algorithms for Fuzzy Clustering. Springer, Heidelberg (2008)
Honda, K., Oshio, S., Notsu, A.: Fuzzy co-clustering induced by multinomial mixture models. J. Adv. Comput. Intell. Intell. Inf. 19(6), 717–726 (2015)
Rigouste, L., Cappé, O., Yvon, F.: Inference and evaluation of the multinomial mixture model for text clustering. Inf. Process. Manag. 43(5), 1260–1280 (2007)
Honda, K., Nakano, T., Oh, C.-H., Ubukata, S., Notsu, A.: Partially exclusive item partition in MMMs-induced fuzzy co-clustering and its effects in collaborative filtering. J. Adv. Comput. Intell. Intell. Inf. 19(6), 810–817 (2015)
Nakano, T., Honda, K., Ubukata, S., Notsu, A.: MMMs-Induced fuzzy co-clustering with exclusive partition penalty on selected items. In: Huynh, V.-N., Inuiguchi, M., Denoeux, T. (eds.) IUKM 2015. LNCS (LNAI), vol. 9376, pp. 226–235. Springer, Heidelberg (2015). doi:10.1007/978-3-319-25135-6_22
Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Stat. Soc. B 39, 1–38 (1977)
Hathaway, R.J.: Another interpretation of the EM algorithm for mixture distributions. Stat. Probab. Lett. 4, 53–56 (1986)
Miyamoto, S., Mukaidono, M.: Fuzzy \(c\)-means as a regularization and maximum entropy approach. In: Proceedings of the 7th International Fuzzy Systems Association World Congress, vol. 2, pp. 86–92 (1997)
Ichihashi, H., Miyagishi, K., Honda, K.: Fuzzy c-means clustering with regularization by K-L information. In: Proceedings of 10th IEEE International Conference on Fuzzy Systems, vol. 2, pp. 924–927 (2001)
Hathaway, R.J., Davenport, J.W., Bezdek, J.C.: Relational duals of the \(c\)-means clustering algorithms. Pattern Recogn. 22(2), 205–212 (1989)
Honda, K., Notsu, A., Ichihashi, H.: Fuzzy PCA-guided robust \(k\)-means clustering. IEEE Trans. Fuzzy Syst. 18(1), 67–79 (2010)
Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Inf. Process. Manage. 24(5), 513–523 (1988)
Honda, K., Oh, C.-H., Notsu, A.: Exclusive condition on item partition in fuzzy co-clustering based on K-L information regularization. In: Proceedings of the Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems, pp. 1413–1417 (2014)
Honda, K., Muranishi, M., Notsu, A., Ichihashi, H.: FCM-type cluster validation in fuzzy co-clustering and collaborative filtering applicability. Int. J. Comput. Sci. Netw. Secur. 13(1), 24–29 (2013)
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This work was supported in part by JSPS KAKENHI Grant Number JP26330281.
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Nakano, T., Honda, K., Ubukata, S., Notsu, A. (2016). Exclusive Item Partition with Fuzziness Tuning in MMMs-Induced Fuzzy Co-clustering. In: Huynh, VN., Inuiguchi, M., Le, B., Le, B., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2016. Lecture Notes in Computer Science(), vol 9978. Springer, Cham. https://doi.org/10.1007/978-3-319-49046-5_16
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