Session based Collaborative Filtering for web page Recommender (SCFR) System based on clustering

Poornalatha, G and Raghavendra, Prakash S (2016) Session based Collaborative Filtering for web page Recommender (SCFR) System based on clustering. In: ICICA, 20/12/2016, D Y Patil College of Engineering, Akurdi, Pune.

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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: Conference or Workshop Item (Paper)
Uncontrolled Keywords: collaborative filtering, k-means, server log, session.
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 13 Jan 2017 08:54
Last Modified: 13 Jan 2017 08:54
URI: http://eprints.manipal.edu/id/eprint/148073

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