Spectral clustering has attracted much research interest in recent years since it can yield impressively good clustering results. Traditional spectral clustering algorithms first s...
Bo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Yin...
Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/...
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...
We study the interaction between global and local techniques in data mining. Specifically, we study the collections of frequent sets in clusters produced by a probabilistic clust...
Image clustering is useful in many retrieval and classification applications. The main goal of image clustering is to partition a given dataset into salient clusters such that the...