Modelling the information seeking user by the decision they make

Bruza, Peter D., Zuccon, Guido, & Sitbon, Laurianne (2013) Modelling the information seeking user by the decision they make. In Clarke, C.L.A., Freund, L., Smucker, M.D., & Yilmaz, E. (Eds.) Proceedings of the 36th Annual ACM SIGIR Conference : Workshop on Modeling User Behavior for Information Retrieval Evaluation (MUBE 2013), ACM, Dublin, Ireland, pp. 5-6.

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The article focuses on how the information seeker makes decisions about relevance. It will employ a novel decision theory based on quantum probabilities. This direction derives from mounting research within the field of cognitive science showing that decision theory based on quantum probabilities is superior to modelling human judgements than standard probability models [2, 1]. By quantum probabilities, we mean decision event space is modelled as vector space rather than the usual Boolean algebra of sets. In this way,incompatible perspectives around a decision can be modelled leading to an interference term which modifies the law of total probability. The interference term is crucial in modifying the probability judgements made by current probabilistic systems so they align better with human judgement. The goal of this article is thus to model the information seeker user as a decision maker. For this purpose, signal detection models will be sketched which are in principle applicable in a wide variety of information seeking scenarios.

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ID Code: 61964
Item Type: Conference Paper
Refereed: Yes
Keywords: Decisions, Relevance, Quantum probability, Modelling, Human judegements
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 21 Aug 2013 23:46
Last Modified: 25 Mar 2014 07:29

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