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...
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Text clustering is one of the difficult and hot research fields in the text mining research. Combing Map Reduce framework and the neuron initialization method of VPSOM (vector pre...