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An adaptive contextual quantum language model

Li, Jingfei; Zhang, Peng; Song, Dawei and Hou, Yuexian (2016). An adaptive contextual quantum language model. Physica A: Statistical Mechanics and its Applications, 456 pp. 51–67.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1016/j.physa.2016.03.003
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Abstract

User interactions in search system represent a rich source of implicit knowledge about the user’s cognitive state and information need that continuously evolves over time. Despite of massive efforts that have been made to exploiting and incorporating this implicit knowledge in information retrieval, it is still a challenge to effectively capture the term dependencies and the user’s dynamic information need (reflected by query modifications) in the context of user interaction. To tackle these issues, motivated by the recent Quantum Language Model (QLM), we develop a QLM based retrieval model for session search, which naturally incorporates the complex term dependencies occurring in user’s historical queries and clicked documents with density matrices. In order to capture the dynamic information within users’ search session, we propose a density matrix transformation framework and further develop an adaptive QLM ranking model. Extensive comparative experiments show the effectiveness of our session quantum language models.

Item Type: Journal Item
Copyright Holders: 2016 Elsevier
ISSN: 0378-4371
Project Funding Details:
Funded Project NameProject IDFunding Body
Key Basic Research Project, 973 Program2013CB329304Chinese National Program
Key Basic Research Project, 973 Program2014CB744604Chinese National Program
Chinese 863 Program2015AA015403Not Set
Not Set61272265Natural Science Foundation of China
Not Set61402324Natural Science Foundation of China
Tianjin Research Program of Application Foundation and Advanced Technology15JCQNJC41700Not Set
Keywords: Quantum language model; Density matrix transformation; Session search; Query change information
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 45876
Depositing User: Dawei Song
Date Deposited: 29 Mar 2016 14:54
Last Modified: 07 Dec 2018 22:52
URI: http://oro.open.ac.uk/id/eprint/45876
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