Modeling user knowledge from queries: Introducing a metric for knowledge

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Abstract

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. © 2010 Springer-Verlag.

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APA

Van Der Sluis, F., & Van Den Broek, E. L. (2010). Modeling user knowledge from queries: Introducing a metric for knowledge. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6335 LNCS, pp. 395–402). https://doi.org/10.1007/978-3-642-15470-6_41

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