Well-organized Data Mining Techniques for Clustering of Users on Web Log Data

Authors(1) :-Avula Chitty

Web usage mining is one among the essential frameworks to find domain data from the interaction of users with the net. This domain data is used for effective management of prognosticative websites, the creation of adaptative websites, enhancing business and net services, personalization, and so on. In nonprofit able organization’s web site, it's tough to spot who area unit users, what info they have, and their interest’s modification with time. Web usage mining supported log knowledge provides an answer to the present problem. The planned work focuses on weblog knowledge preprocessing, thin matrix construction supported net navigation of every user and clump the users of comparable interests. The performance of net usage mining is additionally compared supported k-means, X-means, and farthest 1st clump algorithms.

Authors and Affiliations

Avula Chitty
Department of CSE, Assistant Professor, Sri Indu College of Engineering and Technology, Hyderabad, Telangana, India

Web usage mining, sparse matrix, Clustering, Influence degree, K-means, X-means and farthest first algorithm

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Publication Details

Published in : Volume 4 | Issue 2 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 482-490
Manuscript Number : IJSRST1841124
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Avula Chitty, " Well-organized Data Mining Techniques for Clustering of Users on Web Log Data", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 2, pp.482-490, January-February-2018.
Journal URL : https://ijsrst.com/IJSRST1841124
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