Modeling user knowledge from queries: Introducing a metric for knowledge

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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.

Original languageEnglish
Title of host publicationActive Media Technology - 6th International Conference, AMT 2010, Proceedings
Number of pages8
Publication date2010
Pages395-402
ISBN (Print)3642154697, 9783642154690
DOIs
Publication statusPublished - 2010
Event2010 6th International Conference on Active Media Technology, AMT 2010 - Toronto, ON, Canada
Duration: 28 Aug 201030 Aug 2010

Conference

Conference2010 6th International Conference on Active Media Technology, AMT 2010
LandCanada
ByToronto, ON
Periode28/08/201030/08/2010
SponsorYork University, University of Regina
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6335 LNCS
ISSN0302-9743

ID: 337216111