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QIRM: A quantum interactive retrieval model for session search.

Authors :
Wang, Panpan
Hou, Yuexian
Li, Zhao
Zhang, Yazhou
Source :
Neurocomputing. Sep2021, Vol. 451, p57-66. 10p.
Publication Year :
2021

Abstract

Web search has become a popular way for people to obtain information. Due to the complexity of search task, one retrieval cannot serve all of user's information needs. Multiple interactions with the search engine are required, and session search comes into being. Currently proposed session search methods still cannot take advantage of interactive information to capture the user's implicit information needs. Recently, quantum theory has been successively applied into information retrieval task. We find the similarities between quantum measurements and session interactions. This paper thus develops a Quantum Interactive Retrieval Model (QIRM), which involves both quantum standard measurement (QSM) and quantum weak measurement (QWM) to re-characterize the user's cognition shifts during a session interaction. Particularly, the user's cognition states in strong interaction and weak interaction are quantified into quantum-like representations formalized by QSM and QWM, respectively. The representations are then viewed as the user's information needs for computing ranking score of an evaluated document. We conduct experiments on TREC 2013 and 2014 Session Track datasets. The empirical evaluation demonstrates the effectiveness of our proposed methods, which obtains very comparable performance in terms of nDCG@10 and ERR@10. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
451
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
150770430
Full Text :
https://doi.org/10.1016/j.neucom.2021.04.013