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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 6, ISSUE 4, APRIL 2017

Recommendation Systems for E-Commerce: A Review

Priya S, Mansoor Hussain D

DOI: 10.17148/IJARCCE.2017.6496

Abstract: Recommendation as a social process plays ansignificant role wherepeople rely on external knowledge to make decisions about an artifact of interest. Recommendation system is an intelligent system that generates a ranked list of items on which a user might be interested. Nowadays, there is a big variety of different approaches and algorithms for data filtering and recommendation giving.Recommendation techniques can be classified into three major divisions: Collaborative Filtering, Content Based and Hybrid Recommendations.This paper compares and elaborates these approaches and discusses their limitations by describing the problems suffered by recommendation techniques.



Keywords: Recommendation system, Content-Based Recommendation, collaborative filtering, coldstart, scalablility.

How to Cite:

[1] Priya S, Mansoor Hussain D, “Recommendation Systems for E-Commerce: A Review,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2017.6496