A Hybrid Collaborative Filtering Algorithm for Hotel Recommendation
- DOI
- 10.2991/icmeit-16.2016.65How to use a DOI?
- Keywords
- Recommendation, Collaborative Filtering, Item-based, User-based, Hybrid
- Abstract
Recommendation systems apply knowledge discovery techniques to the problem of making personalized recommendation for information, products or services in the Internet. These works, especially collaborative filtering algorithms acquired relatively satisfactory results. They can millions of users easily search hundreds of millions of items. In tourism industry, potential customers may book hotel just once, which make it very important to recommend them suitable hotel. In this paper, user-based and item-based collaborative filtering methods have been proposed for hotel recommendation. Then we combine them to achieve better effectiveness. Experimental result demonstrates that our hybrid collaborative filtering algorithms outperform existing approaches.
- Copyright
- © 2016, 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 - Ling Shen AU - Qingxi Peng PY - 2016/08 DA - 2016/08 TI - A Hybrid Collaborative Filtering Algorithm for Hotel Recommendation BT - Proceedings of the 2016 International Conference on Mechatronics Engineering and Information Technology PB - Atlantis Press SP - 343 EP - 346 SN - 2352-5401 UR - https://doi.org/10.2991/icmeit-16.2016.65 DO - 10.2991/icmeit-16.2016.65 ID - Shen2016/08 ER -