An Intelligent Recommendation Method for Service Personalized Customization

被引：5
|
作者：
Li, Qi [1 ]
Miao, Rui [1 ]
Zhang, Jie [2 ]
Deng, Xiaoxu [3 ]
机构：
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R China
[2] Donghua Univ, Coll Mech Engn, Shanghai, Peoples R China
[3] Shanghai Jiao Tong Univ, Sch Phys & Astron, Shanghai, Peoples R China
来源：
IFAC PAPERSONLINE | 2019年 / 52卷 / 13期
关键词：
service personalized customization; intelligent recommendation; customization priority; user preference degree; SYSTEMS;
D O I：
10.1016/j.ifacol.2019.11.419
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An intelligent recommendation method for service personalized customization is proposed. Fuzzy theory is applied to determine the customization priority of the service modules based on user's demands User interest degree, option similarity degree based on collaborative association, and option compatibility degree are calculated based on the customized packages and the historical customization records. User preference degree for the options is thus obtained to determine the recommending items and order. In this way, users are step by step recommended to choose service options, in order to complete service customization. Taking a behavior experiment for personalized customization of an electric vehicle lease company as a case, the simulation of service personalized customization and algorithm process is carried out to verify the feasibility and effectiveness of the recommending method, providing scientific and effective recommending methods for related companies in service personalized customization. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：1543 / 1548
页数：6
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