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

摘要：

　　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.

关键词： Information fusion Genetic algorithm Evidence theory Intelligent recommendation

作者: Xiaoyin Xu Lihong Ren Yongsheng Ding

作者单位: College of Information Sciences and Technology College of Information Sciences and Technology;Engineering Research Center of Digitized Textile & Fa

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 2382-2385

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）