High Quality Assessment of Similarity by Using Multiple View Points

Provided by: International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE)
Topic: Data Management
Format: PDF
Clustering is a process of grouping objects based on certain similarity measure. Then groups are known as clusters which can be analyzed and used further for operations like query processing. Clustering algorithms assume certain relationship among objects in the given dataset. The existing clustering algorithms with respect to text mining use single viewpoint similarity measure for partitioned clustering of objects. The main drawback of these algorithms is that the resultant clusters can't make use of fully informative assessment. In this paper, the authors propose a new measure for finding similarity between objects which is multi-viewpoint based.

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