Title: Generation of web recommendations using implicit user feedback and normalised mutual information

Authors: V.S. Dixit; Punam Bedi; Harita Mehta

Addresses: Computer Science Department, Atma Ram Sanatam Dharam College, University of Delhi, South Campus, Delhi, 110021, India ' Department of Computer Science, Faculty of Mathematical Sciences, University of Delhi, North Campus, Delhi, 110007, India ' Computer Science Department, Acharya Narender Dev College, University of Delhi, Govind Puri, Kalkaji, New Delhi, 110019, India

Abstract: The knowledge base of a traditional web recommender system is constructed from web logs, reflecting past user preferences which may change over time. In this paper, an algorithm, based on implicit user feedback on top N recommendations and normalised mutual information, is proposed for collaborative personalised web recommender system. The proposed algorithm updates the knowledge base taking into account the changing user preferences, in order to generate better recommendations in future. The proposed approach and collaborative personalised web recommender systems without feedback are compared. Significant improvements are observed in precision, recall and F1 measure for proposed approach.

Keywords: collaborative web recommender systems; implicit user feedback; item entropy; mutual information; web recommendation systems; personalised web recommender systems; user preferences.

DOI: 10.1504/IJKWI.2013.056362

International Journal of Knowledge and Web Intelligence, 2013 Vol.4 No.2/3, pp.113 - 141

Received: 24 Mar 2012
Accepted: 04 Dec 2012

Published online: 26 Jul 2014 *

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