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Power‐average‐operator‐based hybrid multiattribute online product recommendation model for consumer decision‐making
International Journal of Intelligent Systems ( IF 7 ) Pub Date : 2021-03-08 , DOI: 10.1002/int.22394
Zhen‐Song Chen 1, 2 , Lan‐Lan Yang 1 , Rosa M. Rodríguez 3 , Sheng‐Hua Xiong 4 , Kwai‐Sang Chin 2 , Luis Martínez 3
Affiliation  

This study develops a power‐average‐operator‐based hybrid multiattribute online product recommendation model that considers the consumer's risk attitude to rank categoric product options as a complement to existing recommender systems. Online production recommendation plays a key role in the development of e‐commerce, and can greatly improve consumers' shopping experiences. However, few online shopping sites provide interactive decision aids for consumers such that they can articulate their preferences towards multiple selection attributes with the purpose of mitigating choice difficulty and improving decision quality. Additionally, consumers' risk attitudes to online shopping dramatically impact their product choices. In the model proposed in this paper, the risk attitude‐based power average (RAPA) operator is used to integrate the risk attitude of the decision‐maker into the information fusion process of multiple attribute decision‐making. Subsequently, the risk attitude function, with several basic types, is introduced to quantify the risk attitude of the decision‐maker for use in the RAPA operator. A proportional hesitant fuzzy 2‐tuple linguistic term set (PHF2TLTS) is constructed by incorporating a binary of linguistic information aiming to comprehensively analyze the hybrid product information. With a focus on the information fusion process, the proportional hesitant 2‐tuple linguistic RAPA operator and weighted proportional hesitant 2‐tuple linguistic RAPA operator are introduced to aggregate a given set of PHF2TLTSs. The validity of the proposed model is demonstrated using an illustrative example, a comparison with existing approaches and detailed explanations of the performance differences.

中文翻译:

用于消费者决策的基于功率平均-运算符的混合多属性在线产品推荐模型

这项研究开发了一种基于功率平均-运营商的混合多属性在线产品推荐模型,该模型考虑了消费者的风险态度,以对分类产品选项进行排名,作为对现有推荐系统的补充。在线产品推荐在电子商务的发展中起着关键作用,可以极大地改善消费者的购物体验。但是,很少有在线购物网站为消费者提供交互式决策辅助工具,以便他们可以减轻选择难度并提高决策质量,从而针对多种选择属性阐明自己的偏好。此外,消费者对在线购物的风险态度极大地影响了他们的产品选择。在本文提出的模型中,基于风险态度的平均功率(RAPA)运算符用于将决策者的风险态度整合到多属性决策的信息融合过程中。随后,引入了具有几种基本类型的风险态度函数,以量化供RAPA运营商使用的决策者的风险态度。通过并入旨在综合分析混合产品信息的语言信息二进制,构造了比例犹豫的模糊2元组语言术语集(PHF2TLTS)。着重于信息融合过程,引入了比例犹豫的2元组语言RAPA算子和加权比例犹豫的2元组语言RAPA算子来聚合一组给定的PHF2TLTS。
更新日期:2021-04-27
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