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论文摘要

基于灰色关联度和AHP的用户满意度综合评价模型

Comprehensive Evaluation Model of Users’ Satisfaction Based on Gray Relational Analysis and AHP

作者:陈伟鹏(四川大学计算机学院);柳戌昊(四川省科技信息研究所);唐宁九(四川大学计算机学院);林涛(四川大学计算机学院);刘雯晶(四川省科技信息研究所);彭舰(四川大学计算机学院)

Author:CHEN Wei-Peng(College of Computer Science, Sichuan University);LIU Xu-Hao(Research Institute of Science & Technology Information of Sichuan Province);TANG Ning-Jiu(College of Computer Science, Sichuan University);LIN Tao(College of Computer Science, Sichuan University);LIU Wen-Jing(Research Institute of Science & Technology Information of Sichuan Province);PENG Jian(College of Computer Science, Sichuan University)

收稿日期:2016-09-21          年卷(期)页码:2017,54(4):713-720

期刊名称:四川大学学报: 自然科学版

Journal Name:Journal of Sichuan University (Natural Science Edition)

关键字:满意度评价;可用性;灰色关联度;AHP

Key words:Satisfaction Evaluation; Usability; Grey Relational Analysis; AHP;

基金项目:四川省科技厅支撑项目(2013GZX0138);四川省教育厅重点项目(15ZA0324)

中文摘要

针对信息不明确、评价指标关系复杂的用户评论,难以有效对产品可用性的进行综合评价的问题,提出了一种灰色关联度和AHP(Analytic Hierarchy Process)结合的评模型分析应用到产品可用性研究。利用AHP方法确定在评价指标的相对权重来增强灰色关联度分析的客观性,以此建立产品的用户满意度综合评价模型。在不同价位的手机产品数据集上进行了对比实验,该模型所得的满意度评价排名与实际产品销售排名基本一致。此外,实验也证明了灰色关联度分析能更清晰的区分产品间的满意度差异。上述结论说明在评估信息不完备情况下,提出的模型能够有效的综合评价产品的用户满意度。

英文摘要

For the issue of less effective usability comprehensive evaluation on users’ comments with uncertain information and complex evaluation indexes, a users’ satisfaction comprehensive evaluation model is applied on usability research of production, which integrates gray relational analysis and AHP (Analytic Hierarchy Process). In order to enhance the objective of gray relational analysis, AHP method is used to determine the relative weights of evaluation index so as to establish comprehensive evaluation model of users’ satisfaction model. With contrast experiment on the dataset of smart mobiles in different price, the satisfaction rank from our model is very similar to the one of actual sales. In addition, experiment result shows gray relational analysis can distinguish the satisfaction difference of productions more clearly. So above experiment results illuminate our model can comprehensively effectively evaluate users’ satisfaction of production with incomplete assessment information

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