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Automata modeling for cognitive interference in users relevance judgment

Zhang, Peng; Song, Dawei; Hou, Yuexian; Wang, Jun and Bruza, Peter (2010). Automata modeling for cognitive interference in users relevance judgment. In: AAAI-Fall 2010 Symposium on Quantum Informatics for Cognitive, Social, and Semantic Processes (QI2010), 11-13 Nov 2010, Washington DC, USA.

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Quantum theory has recently been employed to further ad- vance the theory of information retrieval (IR). A challenging research topic is to investigate the so called quantum-like interference in users’ relevance judgment process, where users are involved to judge the relevance degree of each document with respect to a given query. In this process, users’ relevance judgment for the current document is often interfered by the judgment for previous documents, due to the interference on users’ cognitive status. Research from cognitive science has demonstrated some initial evidence of quantum-like cogni- tive interference in human decision making, which underpins the user’s relevance judgment process. This motivates us to model such cognitive interference in the relevance judgment process, which in our belief will lead to a better modeling and explanation of user behaviors in relevance judgement process for IR and eventually lead to more user-centric IR models. In this paper, we propose to use probabilistic automaton (PA) and quantum finite automaton (QFA), which are suitable to represent the transition of user judgment states, to dynamically model the cognitive interference when the user is judging a list of documents.

Item Type: Conference or Workshop Item
Copyright Holders: 2010 Association for the Advancement of Artificial Intelligence
Extra Information: pp.125-133
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 35120
Depositing User: Dawei Song
Date Deposited: 01 Nov 2012 10:53
Last Modified: 09 Dec 2018 04:58
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