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Aggregate Profiling for Recommendation of web pages using SOM and K-Means Clustering Techniques

by Shveta Kundra Bhatia, Harita Mehta, Veer Sain Dixit
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 36 - Number 9
Year of Publication: 2011
Authors: Shveta Kundra Bhatia, Harita Mehta, Veer Sain Dixit
10.5120/4518-6406

Shveta Kundra Bhatia, Harita Mehta, Veer Sain Dixit . Aggregate Profiling for Recommendation of web pages using SOM and K-Means Clustering Techniques. International Journal of Computer Applications. 36, 9 ( December 2011), 13-20. DOI=10.5120/4518-6406

@article{ 10.5120/4518-6406,
author = { Shveta Kundra Bhatia, Harita Mehta, Veer Sain Dixit },
title = { Aggregate Profiling for Recommendation of web pages using SOM and K-Means Clustering Techniques },
journal = { International Journal of Computer Applications },
issue_date = { December 2011 },
volume = { 36 },
number = { 9 },
month = { December },
year = { 2011 },
issn = { 0975-8887 },
pages = { 13-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume36/number9/4518-6406/ },
doi = { 10.5120/4518-6406 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:22:43.207530+05:30
%A Shveta Kundra Bhatia
%A Harita Mehta
%A Veer Sain Dixit
%T Aggregate Profiling for Recommendation of web pages using SOM and K-Means Clustering Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 36
%N 9
%P 13-20
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Since, number of users are increasing exponentially so proper analysis of such data by devising efficient algorithms is essential which ultimately helps in determining the life time value of customers and judging the effectiveness of promotional campaigns as well. Better services and quality can be provided by mining the web access log files. In this paper, we have shown that with the help of clustering techniques, Self Organized Feature Maps and K-Means useful knowledge is extracted. We have also proposed to derive the interest and behavior of a significant group of users by applying the concept of “Aggregate Usage Profile”. Further, this technique has been used for looking frequently accessed pages for recommendations.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Web Usage Mining K-Means Self-Organizing Feature Maps Aggregate Usage Profile

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