Distributed Document Clustering Using K-Means

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Document clustering, one of the traditional data mining techniques, is an unsupervised learning paradigm where clustering methods try to identify inherent grouping of the text documents. The importance of document clustering emerges from the massive volumes of textual documents created. Also, with more and more development of information technology, data set in many domains is reaching beyond peta-scale; making it difficult to work with the document clustering algorithms in central site and leading to the need of increasing the computational requirements. The concept of distributed computing thus; is explored for document clustering giving rise to distributed document clustering.

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