基于用户满意度的学术文献推荐评价研究被引量：4

Research on User Satisfaction-based paper recommendation evolution

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摘要学术文献推荐可以自动化地为学者推荐合适的文献。借助于文献推荐,用户可以在一定程度上提高文献检索的效率。鉴于当前对文献推荐的评价缺少实证研究,本文从文献推荐的内容质量、服务质量和技术能力三个方面,检验其对用户满意度和持续使用意愿的影响关系。利用量表式问卷对网络用户进行调查,通过结构方程建模的方法对所回收的问卷进行分析。用户使用文献推荐服务的满意度受到推荐内容质量、服务质量和技术能力的影响,进而影响其持续使用意愿。 Paper recommendation can recommend suitable documents for an author. With the aid of paper recommendation, authors can improve the efficiency of retrieving academic literatures. Due to the lack of empirical study on paper recommendation evolution, this paper aims at exploring the interaction on user satisfaction and continuing use willingness for three aspects such as recommended content quality, service quality and technical capacity. This paper collects 299 valid questionnaires with questionnaires scale for users, and analyzes the samples by means of structural equation modeling （SEM）. We find that recommended content quality, service quality and technical capacity have positive effects on user satisfaction, and further have positive effects on users＇ continuing use willingness.

作者陈海华何文静

机构地区武汉大学信息管理学院武汉大学信息检索与知识挖掘研究所

出处《数字图书馆论坛》 CSSCI 2016年第4期22-29,共8页 Digital Library Forum

关键词学术文献推荐推荐内容质量服务质量技术能力用户满意度 Paper Recommendation Recommended Content Quality Service Quality Technical Capacity User Satisfaction

分类号 G252 [文化科学—图书馆学]

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参考文献24

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