Farthest Neighbor Approach for Finding Initial Centroids in K-Means

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Provided by: Computer Science Journals
Topic: Data Management
Format: PDF
Text document clustering is gaining popularity in the knowledge discovery field for effectively navigating, browsing and organizing large amounts of textual information into a small number of meaningful clusters. Text mining is a semi-automated process of extracting knowledge from voluminous unstructured data. A widely studied data mining problem in the text domain is clustering. Clustering is an unsupervised learning method that aims to find groups of similar objects in the data with respect to some predefined criterion. In this paper, the authors propose a variant method for finding initial centroids.
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