This paper investigates the applicability of distributed clustering technique, called RACHET [1], to organize large sets of distributed text data. Although the authors of RACHET c...
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
—A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. How...
Stream data is common in many applications, e.g., stock quotes, merchandize sales record, system logs, etc.. It is of great importance to analyze these stream data. As one of the ...
Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large sets of documents into a small number of meaningful ...