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A quasi-current representation for information needs inspired by Two-State Vector Formalism

Wang, Panpan; Hou, Yuexian; Li, Jingfei; Zhang, Yazhou; Song, Dawei and Li, Wenjie (2017). A quasi-current representation for information needs inspired by Two-State Vector Formalism. Physica A: Statistical Mechanics and its Applications, 482 pp. 627–637.

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Recently, a number of quantum theory (QT)-based information retrieval (IR) models have been proposed for modeling session search task that users issue queries continuously in order to describe their evolving information needs (IN). However, the standard formalism of QT cannot provide a complete description for users’ current IN in a sense that it does not take the ‘future’ information into consideration. Therefore, to seek a more proper and complete representation for users’ IN, we construct a representation of quasi-current IN inspired by an emerging Two-State Vector Formalism (TSVF). With the enlightenment of the completeness of TSVF, a “two-state vector” derived from the ‘future’ (the current query) and the ‘history’ (the previous query) is employed to describe users’ quasi-current IN in a more complete way. Extensive experiments are conducted on the session tracks of TREC 2013 & 2014, and show that our model outperforms a series of compared IR models.

Item Type: Journal Item
Copyright Holders: 2017 Elsevier B.V.
ISSN: 0378-4371
Keywords: Information Retrieval; Two-State Vector Formalism; Quantum theory; Session search
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 53835
Depositing User: ORO Import
Date Deposited: 15 Mar 2018 10:04
Last Modified: 29 Jun 2020 13:59
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