User behavior analysis of the open-ended document classification system

Authors:
Yang Sok Kim;Byeong Ho Kang;Young Ju Choi;SungSik Park;Gil Cheol Park;Seok Soo Kim
Affiliations:
School of Computing, University of Tasmania, Sandy Bay, Tasmania, Australia;School of Computing, University of Tasmania, Sandy Bay, Tasmania, Australia;School of Computing, University of Tasmania, Sandy Bay, Tasmania, Australia;School of Computing, University of Tasmania, Sandy Bay, Tasmania, Australia;School of Information & Multimedia, Hannam University, Daejeon, Korea;School of Information & Multimedia, Hannam University, Daejeon, Korea
Venue:
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Year:
2006

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Abstract

Real-world document classification is an open-ended problem, rather than a close-ended problem, because the document classification domain continually evolves as the time passes. Unlike the close-ended document classification, the participants in the open-ended problem actively take part in the problem solving process. For this reason, it is important to understand the problem solver's behavioral characteristics. This paper proposes a thorough analysis of them. We found that the problem solving strategies are significantly different among participants because of individual differences in cognition among participants.