An Improved D-S Evidence Theory based on Genetic Algorithm to VIP Intelligent Recognition and Recommendation System

DOI

10.2991/iccsee.2013.596How to use a DOI?

Keywords

Information fusion, Genetic algorithm, Evidence theory, Intelligent recommendation

Abstract

In this paper, we use GA to improve the D-S evidence theory, and apply the improved D-S evidence theory to VIP intelligent recognition and recommendation system. In the VIP intelligent recognition and recommendation system of clothes, there are three main evidences: body size, personal preferences, and purchase records. So collision often happens inevitable. This requirement asks us to find out a suitable method to identify the VIPs’ needs. D-S evidence theory can improve the rate of identification, but has no idea about the collision. The improved D-S evidence theory based on genetic algorithm can deal with the collision evidence and improve the rate of the identification and the stability. As such we can provide VIP more suitable recommendation. The experiment results of clothes recommendation demonstrate the flexibility of the improved method.

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  - Xiaoyin Xu
AU  - Lihong Ren
AU  - Yongsheng Ding
PY  - 2013/03
DA  - 2013/03
TI  - An Improved D-S Evidence Theory based on Genetic Algorithm to VIP Intelligent Recognition and Recommendation System
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2381
EP  - 2384
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.596
DO  - 10.2991/iccsee.2013.596
ID  - Xu2013/03
ER  -