Document Clustering on Various Similarity Measures

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Clustering is a useful technique that organizes a large quantity of unordered text documents into a small number of meaningful and coherent clusters, thereby providing a basis for intuitive and informative navigation and browsing mechanisms. A wide variety of distance functions and similarity measures have been used for clustering. In this paper, the authors mainly focus on different similarity measures, view points and Document clustering. They introduce a novel multi-viewpoint based similarity measure and two related clustering methods. Using multiple viewpoints, more informative assessment of similarity could be achieved.

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