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

International Journal of Computer Applications
© 2011 by IJCA Journal
Volume 36 - Number 9
Year of Publication: 2011
Shveta Kundra Bhatia
Harita Mehta
Veer Sain Dixit

Shveta Kundra Bhatia, Harita Mehta and Veer Sain Dixit. Article: Aggregate Profiling for Recommendation of web pages using SOM and K-Means Clustering Techniques. International Journal of Computer Applications 36(9):13-20, December 2011. Full text available. BibTeX

	author = {Shveta Kundra Bhatia and Harita Mehta and Veer Sain Dixit},
	title = {Article: Aggregate Profiling for Recommendation of web pages using SOM and K-Means Clustering Techniques},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {36},
	number = {9},
	pages = {13-20},
	month = {December},
	note = {Full text available}


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.


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