Abstract- The large majority of existing clustering algorithms are centered around the notion of a feature, that is, individual data items are represented by their intrinsic proper...
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
Abstract. In this paper we propose a clustering algorithm called sCluster for analysis of gene expression data based on pattern-similarity. The algorithm captures the tight cluster...
Xiangsheng Chen, Jiuyong Li, Grant Daggard, Xiaodi...
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...
Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock,...
Joachim Gudmundsson, Marc J. van Kreveld, Bettina ...