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

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.

• Periodical: Applied Mechanics and Materials (Volumes 347-350)
• Pages: 2442-2446
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.347-350.2442
• Online since: August 2013
• Authors: Xiao Yin Xu, Li Hong Ren, Yong Sheng Ding
• Keywords: Evidence Theory, Genetic Algorithm (GA), Information Fusion, Intelligent Recommendation

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