A Collaborative Filtering Algorithm Combined with User Habits for Rating

DOI

10.2991/lemcs-15.2015.255How to use a DOI?

Keywords

Collaborative filtering; Personalized recommendation; User habits for rating; Bhattacharyya Coefficient; Entropy

Abstract

Collaborative filtering is one of the most successful and widely used technologies in personalized recommendation systems. This paper proposed a novel algorithm combined with user habits for rating as the conventional method leads lower accuracy relatively. In order to reveal the hidden relationship between users, the new algorithm not only reserves the traditional measure but also takes Bhattacharyya Coefficient and entropy into account while calculating the user similarities. Experiment results show the new algorithm outperforms the conventional method.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Min Li
AU  - Kai Zheng
PY  - 2015/07
DA  - 2015/07
TI  - A Collaborative Filtering Algorithm Combined with User Habits for Rating
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 1279
EP  - 1282
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-15.2015.255
DO  - 10.2991/lemcs-15.2015.255
ID  - Li2015/07
ER  -