The Application of Social Tagging Based Collaborative Filtering Personal Recommender Strategy in Electricity Market
- DOI
- 10.2991/cisia-15.2015.68How to use a DOI?
- Keywords
- collaborative filtering; recommender system; social tagging; electricity market
- Abstract
In the Internet world, when people access to the information, they are also providing information to others. Therefore, how to find valuable information from the vast amounts of information in order to meet the user's needs, and how to find and enjoy the valuable information by the required users, have been a hot issue which is concerned by academia and the business. Collaborative filtering (CF) and social tagging are the most widely recommendation techniques. In this paper, tag-based collaborative filtering algorithm is proposed to the electricity market. The individual requirement can be satisfied according to different power consumers. This new algorithm can mine the potential preferences of users, and then recommend items in the user's preferences scope. This method can improve the traditional collaborative filtering methods, and can solve the single interest model problem of traditional methods. The experiments based on electricity consumer data set shows that the tag-based collaborative filtering method is significantly better than the traditional collaborative filtering methods in recommendation effects.
- 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/).
Cite this article
TY - CONF AU - J.H Yang AU - H.B Wang AU - C.H Gao AU - Y. Dai AU - Z.L Lv PY - 2015/06 DA - 2015/06 TI - The Application of Social Tagging Based Collaborative Filtering Personal Recommender Strategy in Electricity Market BT - Proceedings of the International Conference on Computer Information Systems and Industrial Applications PB - Atlantis Press SP - 253 EP - 255 SN - 2352-538X UR - https://doi.org/10.2991/cisia-15.2015.68 DO - 10.2991/cisia-15.2015.68 ID - Yang2015/06 ER -