文献类型：期刊文献

英文题名：A Context-Dependent Preference Model Based on Prospect Theory into Critique-Based Recommender System

作者：Wang, Yindi[1]; Yan, Hongbin[1]

机构：[1] School of Business, East China University of Science and Technology, Shanghai, China

年份：2019

卷号：2

起止页码：189

外文期刊名：Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019

收录：EI(收录号：20200408073921)

语种：英文

外文关键词：Decision making - Decision theory - Electronic commerce - Collaborative filtering

摘要：With the development of e-commerce, the number of online products has increased, which created the challenge to selection. The emergence of the recommendation system has alleviated this dilemma. The user-critique-based recommender system can solve the cold start problem of the traditional collaborative filtering algorithm. Some scholars have noticed the context-dependence of user's preferences in the shaping process when interacting with system. However, few studies considered the context-dependence of preferences in specific recommendation algorithms. One of the difficulties is the qualitative and quantitative analysis of the impact of the complex contexts. This paper constructed a decision maker preference model for the user-based recommendation system based on the context-dependent preference model and prospect theory. Then conducted experiment comparing the performance of model and the traditional algorithm in recommendation systems in the single-decision situation. The results showed that our model has better performance in the relevant context. ? 2019 IEEE.