A Novel Hotel Recommendation Model

DOI

10.2991/mmebc-16.2016.292How to use a DOI?

Keywords

Recommendation, Trip, Collaborative Filtering, Item-based

Abstract

With the development of Internet, a large amount of users purchase product, book hotels, buy goods from the web. They also share their experiences on the web. Other users can read the reviews or rating scores to choose the products or services. The user is difficult to read the information, since the data on the web is very huge. Recommendation system is an important technique which produces high quality recommendations. However, the amount of work increases with the number of participants in traditional recommendation system. In this paper, we propose a novel recommendation model which employs user-based collaborative filtering techniques to recognize the user-item matrix. Our experiment on different datasets shows that the proposed model acquires satisfactory performance than existing model.

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/).

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TY  - CONF
AU  - Qingxi Peng
AU  - Ling Shen
PY  - 2016/06
DA  - 2016/06
TI  - A Novel Hotel Recommendation Model
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 1432
EP  - 1435
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.292
DO  - 10.2991/mmebc-16.2016.292
ID  - Peng2016/06
ER  -