Research on LBS-based Optimizing Personal Recommendation System

DOI

10.2991/cse.2013.56How to use a DOI?

Keywords

LBS; collaborative filtering; personal recommendation; optimizing personal recommendation

Abstract

In recent years, more and more internet companies trend to fuse their products with personal recommendation functions which based on a popular technology called LBS (location based service).Although the idea of this business model satisfies the characteristic of Internet industry felicitously, scientists and engineers gradually find out that the effect of the personal recommendation is worse than they expected. Due to the current technology which is not suitable and mature to make a real combination between personal recommendation and LBS module to support the internet applications, there are plenty of problems such as the network environment of the user, the location filtering, user modeling, data sparse and cold start. In this paper, we proposed a novel optimized personal recommendation system, which based on LBS. The system can not only solve the major problems mentioned above but also provide a good recommendation services based on customer’s geographical position. According some statics we evaluate our system in an analog experiment and come to an conclusion that the new one provide a better performance than the traditional ideas.

Copyright

© 2013, 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  - Enhui Li
AU  - Xin Chen
AU  - Taiyan Hao
AU  - Xiangling Fu
PY  - 2013/07
DA  - 2013/07
TI  - Research on LBS-based Optimizing Personal Recommendation System
BT  - Proceedings of the 2nd International Conference on Advances in Computer Science and Engineering (CSE 2013)
PB  - Atlantis Press
SP  - 251
EP  - 255
SN  - 1951-6851
UR  - https://doi.org/10.2991/cse.2013.56
DO  - 10.2991/cse.2013.56
ID  - Li2013/07
ER  -