Clustering methods usually require to know the best number of clusters, or another parameter, e.g. a threshold, which is not ever easy to provide. This paper proposes a new graph-b...
In this paper we present a new parallel clustering algorithm based on the extended star clustering method. This algorithm can be used for example to cluster massive data sets of do...
Ideally, a multi-strategy learning algorithm performs better than its component approaches. RISE is a multi-strategy algorithm that combines rule induction and instance-based learn...
Abstract. We present a new distributed association rule mining (D-ARM) algorithm that demonstrates superlinear speed-up with the number of computing nodes. The algorithm is the fi...
Clustering of data has numerous applications and has been studied extensively. It is very important in Bioinformatics and data mining. Though many parallel algorithms have been des...