Tourism Information Pushing System Based On Intelligent Recommendation
Authors
Xiaojun Bai, Xiaoxu Zhang, Shuyi Zhang, Lei He
Corresponding Author
Xiaojun Bai
Available Online March 2014.
- DOI
- https://doi.org/10.2991/mce-14.2014.121How to use a DOI?
- Keywords
- Tourism service; Intelligent recommendation; Collaborative filtering; Location based recommendation; Map-Reduce
- Abstract
- User usually retrieve information of interest via search engines, but for a mobile client, the user experience of manually search will be poor, for it is inefficient, and may bring huge data traffic for mobile user. To provide a convenient method for mobile users to obtain tourism information, putting forward a tourism information pushing system based on intelligent recommendation. The item based collaborative filtering rules and the location based recommendation algorithm were introduced to generate recommendation items, and the XMPP based pushing technology was used to push these items to mobile client. By these means, the tourism information will be searched and filtered intelligently according to user’s profile, and pushed to end user automatically, thus provide customized recommendation service for each user, and improve user experience of tourism service platform. To solve the problem of huge data and huge calculating, Map-Reduce optimized algorithm were discussed to improve the efficiency of recommendation creation. Introduced the total structure of this system, the design of each component, as well as the detailed implementation of recommendation algorithm. experiments proved the efficiency of this system.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xiaojun Bai AU - Xiaoxu Zhang AU - Shuyi Zhang AU - Lei He PY - 2014/03 DA - 2014/03 TI - Tourism Information Pushing System Based On Intelligent Recommendation BT - 2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14) PB - Atlantis Press SP - 541 EP - 544 SN - 1951-6851 UR - https://doi.org/10.2991/mce-14.2014.121 DO - https://doi.org/10.2991/mce-14.2014.121 ID - Bai2014/03 ER -