PERFORMANCE ANALYSIS OF K-MEANS ALGORITHMS IN WEBLOG DATA
Journal Title: Elysium Journal of Engineering Research and Management - Year 2016, Vol 3, Issue 4
Abstract
Web mining is used to discover interest patterns which can be applied to many real world problems like refining web sites, better understanding the user behavior, product approval etc. Data mining software is one of a number of analytical tools for analyzing data. In this paper we are studying the various clustering algorithms for segmentation model. The basic idea of clustering is to define the similarity between the distance, the distance that represents the data between the data to measure the similarity of the size of the data are classified, until all the data gathering is completed. Cluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more similar to each other than to those in other clusters. Our main aim to show the performance of K-means algorithm and will be most suitable for the users.
Authors and Affiliations
Abirami K, Mayilvaganan P
Keywords
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