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Modeling User Knowledge from Queries: Introducing a Metric for Knowledge

机译:从查询中建模用户知识:介绍知识的指标

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The user's knowledge plays a pivotal role in the usability and experience of any information system. Based on a semantic network and query logs, this paper introduces a metric for users' knowledge on a topic. The finding that people often return to several sets of closely related, well-known, topics, leading to certain concentrated, highly activated areas in the semantic network, forms the core of this metric. Tests were performed determining the knowledgeableness of 32,866 users on in total 8 topics, using a data set of more than 6 million queries. The tests indicate the feasibility and robustness of such a user-centered indicator.
机译:用户的知识在任何信息系统的可用性和经验中发挥着关键作用。基于语义网络和查询日志,本文介绍了用户对主题知识的指标。发现人们经常返回几套密切相关的,众所周知的主题,导致某些集中,高度激活的区域在语义网络中形成了该度量的核心。使用超过600万个查询的数据集进行了总计8个主题,执行了32,866个用户的测试。测试表明这种用户居中指示器的可行性和稳健性。

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