摘要
【目的/意义】目前FAQ问答系统的评价集中在面向信息检索的客观指标上,为使评价体系更加全面,探索性地从用户体验角度建立FAQ问答系统用户满意度评价指标体系,有助于提升FAQ问答系统服务质量,提高用户满意度。【方法/过程】以高校图书馆问答型机器人为研究对象,依据信息系统成功模型和用户满意度理论,结合用户体验相关指标构建FAQ问答系统用户满意度评价指标体系。通过问卷调研,利用层次分析法和熵权法确立指标权重,并基于调研结果对FAQ问答系统提出相关建议。【结果/结论】FAQ问答系统用户满意度评价指标体系由系统质量、信息质量、服务质量三个一级指标和12个二级指标构成,回答内容完整性、服务界面友好性等指标对用户满意度影响较大,答案准确性、答案时效性、反馈途径存在性和系统特色性四个方面需进一步优化。【创新/局限】构建了FAQ问答系统用户满意度评价指标体系,发掘目前FAQ问答系统中存在的问题并提出相应建议,后续将继续完善评价指标体系。
【Purpose/significance】At present,the evaluation of FAQ QA system focuses on the objective indicators oriented to information retrieval.In order to make the evaluation system more comprehensive,the user satisfaction evaluation index system of FAQ QA system is explored from the perspective of user experience,which helps to improve the service quality of FAQ QA system and improve user satisfaction.【Method/process】Taking the question answering robot of university library as the research object,according to the success model of information system and the theory of user satisfaction,combined with the relevant indicators of user experience,the user satisfaction index system of FAQ question answering system is constructed.Through questionnaire survey,the weights of indicators are determined by using the analytic hierarchy process and entropy weight method,and relevant suggestions are put forward for the FAQ system based on the survey results.【Result/conclusion】The evaluation index system of user satisfaction of FAQ question answering system is composed of three first-level indicators and 12 second-level indicators of system quality,information quality and service quality.The integrity of the answer content and the friendliness of the service interface have a great impact on user satisfaction.The accuracy of the answer,the timeliness of the answer,the existence of feedback channels and the characteristics of the system need to be further optimized.【Innovation/limitation】The evaluation index system of user satisfaction of FAQ QA system has been built,and the existing problems in the current FAQ QA system have been explored and corresponding suggestions have been put forward.The evaluation index system will continue to be improved in the future.
作者
王娜
李杰
WANG Na;LI Jie(School of Information Management,Zhengzhou University,Zhengzhou 450001,China;Zhengzhou Data Science Research Center,Zhengzhou 450001,China)
出处
《情报科学》
CSSCI
北大核心
2023年第9期164-172,共9页
Information Science
基金
郑州大学人文社会科学优秀青年科研团队培育计划项目“用户参与的网络知识服务研究”(2020-QNTD-09)。
