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Using Rough Set in Assessing Website's Service Quality

机译:使用粗糙集评估网站的服务质量

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摘要

At present, people are increasingly dependent on the service of websites to do work and enjoy life. They pay even more attention to the quality of service than that of systems and information of the websites. And there are many academic researchers who have developed instruments to evaluate the service quality of Websites (WebSQ) which include different items from 6 to 156. However, when providing the proposal to the managers to improve the WebSQ effectively and efficiently, people usually analyze the important items instead of all the aspects. And they usually use the method of regression analysis. In his paper we initially introduced attribution reduction of Rough Set (RS) which needs no prior knowledge. The case study shows that RS has another advantage of higher effectiveness over regression analysis. Also, the paper gives the future research directions.
机译:当前,人们越来越依赖网站的服务来工作和享受生活。他们比网站的系统和信息更加关注服务质量。并且有许多学术研究人员开发了评估网站服务质量(WebSQ)的工具,其中包括从6到156的不同项目。但是,当向管理者提供建议以有效和高效地改进WebSQ时,人们通常会分析重要项目,而不是所有方面。而且他们通常使用回归分析的方法。在他的论文中,我们最初介绍了不需要先验知识的粗糙集(RS)的归因减少。案例研究表明,与回归分析相比,RS具有更高的有效性。并且,本文给出了未来的研究方向。

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