The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is then used to nd local minima. In this paper we sh...
Hongyuan Zha, Xiaofeng He, Chris H. Q. Ding, Ming ...
In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...
In this paper we investigate the performance of a Computer Aided Diagnosis (CAD) system for the detection of clustered microcalcifications in mammograms. Our detection algorithm co...
-- This paper proposes to enhance search query log analysis by taking into account the semantic properties of query terms. We first describe a method for extracting a global semant...
Lyes Limam, David Coquil, Harald Kosch, Lionel Bru...
The generation of a set of rules underlying a classification problem is performed by applying a new algorithm, called Hamming Clustering (HC). It reconstructs the and-or expressio...