3clust 2012 - PAKDD Workshop on Multi-view data, High-dimensionality, External Knowledge: Striving for a Unified Approach to Clustering

Despite the advancement in data clustering techniques, the literature still lacks a unified framework capable of handling the ill-posed nature of clustering, the high-dimensionality issue, the often multi-faceted nature of the data, and the opportunity of exploiting application-driven and user-provided knowledge. Such framework would enable clustering solutions for a variety of tasks and applications, including data integration, topic detection and tracking, evolving data management, collaborative filtering, document classification and retrieval, Web data and social network analysis, etc.
In this workshop titled Multi-view data, High-dimensionality, External Knowledge: Striving for a Unified Approach to Clustering, we solicit original papers (including work in progress) that contribute to narrow the aforementioned research gap in data clustering. In particular, we solicit approaches for solving emerging problems such as clustering ensembles, semi-supervised clustering, subspace/projective clustering, co-clustering, and multi-view clustering. Of particular interest will be papers that draw new and insightful connections between these techniques; and papers that contribute to the achievement of a unified framework that combines two or more of these techniques.