Abstract. Clustering is a problem of great practical importance in numerous applications. The problem of clustering becomes more challenging when the data is categorical, that is, ...
Data clustering methods have many applications in the area of data mining. Traditional clustering algorithms deal with quantitative or categorical data points. However, there exist...
Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzew...
Huge amounts of data are available in large-scale networks of autonomous data sources dispersed over a wide area. Data mining is an essential technology for obtaining hidden and v...
Mei Li, Guanling Lee, Wang-Chien Lee, Anand Sivasu...
As organizations accumulate data over time, the problem of tracking how patterns evolve becomes important. In this paper, we present an algorithm to track the evolution of cluster...
Abstract. In this paper we propose the extended star clustering algorithm and compare it with the original star clustering algorithm. We introduce a new concept of star and as a co...