Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Normal mixture models are widely used for statistical modeling of data, including cluster analysis. However maximum likelihood estimation (MLE) for normal mixtures using the EM al...
In many applications extraction of source signals of interest from observed signals maybe is a more feasible approach than simultaneous separation of all the source signals, since...
The spatial clustering of genes across different genomes has been used to study important problems in comparative genomics, from identification of operons to detection of homologo...
We consider a challenging clustering task: the clustering of muti-word terms without document co-occurrence information in order to form coherent groups of topics. For this task, ...