Dear Joel,

Here are references of several some very cited papers that might be relevant for your needs.

Berkhin, P. (2006). A survey of clustering data mining techniques. In Grouping multidimensional data (pp. 25-71). Springer Berlin Heidelberg.‏

Parsons, L., Haque, E., & Liu, H. (2004). Subspace clustering for high dimensional data: a review. ACM SIGKDD Explorations Newsletter, 6(1), 90-105.‏

Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31(8), 651-666.‏

Ng, M. K., & Wong, J. C. (2002). Clustering categorical data sets using tabu search techniques. Pattern Recognition, 35(12), 2783-2790.‏

Modha, D. S., & Spangler, W. S. (2003). Feature weighting in k-means clustering. Machine learning, 52(3), 217-237.‏

Ahmad, A., & Dey, L. (2007). A< i> k-mean clustering algorithm for mixed numeric and categorical data. Data & Knowledge Engineering, 63(2), 503-527.‏

Talavera, L. (2005). An evaluation of filter and wrapper methods for feature selection in categorical clustering. In Advances in Intelligent Data Analysis VI (pp. 440-451). Springer Berlin Heidelberg.‏

Best regards,

Yaakov

Thank you, Yaakov.

I had already found some of these references. But, I'm not an expert in this field. And, due to this, I'm not so confident in my judgments about the relevance of them.

Your suggestions will be very helpful.

Two recent approaches were published in ICTAI 2014:

J. L. Carbonera and M. Abel, “Categorical data clustering:a correlation-based approach for unsupervised attribute weighting,” in Proceedings of ICTAI 2014, 2014.

J. L. Carbonera and M. Abel, “An entropy-based subspace clustering algorithm for categorical data,” in Proceedings of ICTAI 2014, 2014.