A Collaborative Filtering Algorithm Combined with User Habits for Rating
Min Li, Kai Zheng
Available Online July 2015.
- 10.2991/lemcs-15.2015.255How to use a DOI?
- Collaborative filtering; Personalized recommendation; User habits for rating; Bhattacharyya Coefficient; Entropy
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.
- © 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/).
Cite this article
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 -