文章基本信息

标题：Automatic Deep Web Query Results User Satisfaction Evaluation with Click-through Data Analysis
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作者：Zhen Liu ; Yong Feng ; Huijuan Wang 等
期刊名称：International Journal of Smart Home
印刷版ISSN：1975-4094
出版年度：2014
卷号：8
期号：5
页码：25-32
DOI：10.14257/ijsh.2014.8.5.03
出版社：SERSC
摘要：We browse through hundreds of Deep web pages everyday to find information of interest. We feel happy when Deep web browsing operations provide us with necessary information; otherwise, we feel bitter. Now, the measurement of this user satisfaction has become a hot research topic. In this paper, we propose a click-through-data-based and unsupervised user satisfaction evaluation system, CNEITE, to evaluate the user satisfaction of Deep Web query result pages. It applies query type classifying, navigational query evaluating, informational/transactional query evaluating to solve the challenging tasks. We evaluated our CNEITE system on the AOL data sets, experimental results show that CNEITE achieves higher classify precision than a widely used classify method , Dtree, and higher annotate answer accuracy than method proposed in [17].
关键词：Automatic user satisfaction evaluation; Deep Web; click-through data ; analysis