Poornalatha, G and Raghavendra, Prakash S (2017) Session based Collaborative Filtering for web page Recommender (SCFR) System based on clustering. International Journal of Control Theory and Applications, 10 (8). pp. 679-687. ISSN 09745572
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Abstract
With the explosive growth of the world wide web, getting relevant and useful information from vast quantity of data has become a significant problem. Web page recommender system assists user by providing recommendations to ease their navigation through a web site. Many recommender systems have been developed to discover web pages that may be useful to the user. This paper proposes a novel recommender system which adopts the concept of collaborative filtering. The performance of proposed recommender system is evaluated based on precision and recall metrics. Also, results obtained are encouraging in terms of precision and recall compared to couple of other results in the literature
Item Type: | Article |
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Uncontrolled Keywords: | collaborative filtering, k-means, server log, session. |
Subjects: | Engineering > MIT Manipal > Information and Communication Technology |
Depositing User: | MIT Library |
Date Deposited: | 08 Apr 2017 09:11 |
Last Modified: | 08 Apr 2017 09:11 |
URI: | http://eprints.manipal.edu/id/eprint/148654 |
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