Modeling relevance judgement inspired by quantum weak measurement

Panpan Wang; Tianshu Wang; Yuexian Hou; Dawei Song

doi:10.1007/978-3-319-76941-7_32

Modeling relevance judgement inspired by quantum weak measurement

Panpan Wang
, Tianshu Wang
, Yuexian Hou^*
, Dawei Song

^*Corresponding author for this work

Tianjin University
Open University Milton Keynes

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

Concept in Quantum theory (QT) has been successfully inspired analogous concepts in the field of Information Retrieval (IR). Many IR researchers have employed the QT to investigate cognitive phenomena within user behaviors, and also have verified the existence of quantum-like phenomena in real web search. However, for some complex search task, in which user’s information need (IN) is dynamic and hard to be captured, QT currently adopted still can not explain some more complex cognitive phenomena. In this paper, a user experiment is conducted to investigate the variance of relevance judgement, and its results demonstrate that quantum Weak Measurement (WM) is more appropriate than the standard quantum measurement to model relevance judgement. Further, a WM-based session search model (WSM) is presented to model user’s dynamic evolving IN. The extensive experiments are tested on the session track of TREC 2013 & 2014 and verify the effectiveness of WSM.

Original language	English
Title of host publication	Advances in Information Retrieval - 40th European Conference on IR Research, ECIR 2018, Proceedings
Editors	Leif Azzopardi, Gabriella Pasi, Allan Hanbury, Benjamin Piwowarski
Publisher	Springer Verlag
Pages	424-436
Number of pages	13
ISBN (Print)	9783319769400
DOIs	https://doi.org/10.1007/978-3-319-76941-7_32
Publication status	Published - 2018
Externally published	Yes
Event	40th European Conference on Information Retrieval, ECIR 2018 - Grenoble, France Duration: 26 Mar 2018 → 29 Mar 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10772 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	40th European Conference on Information Retrieval, ECIR 2018
Country/Territory	France
City	Grenoble
Period	26/03/18 → 29/03/18

Keywords

Quantum weak measurement
Relevance judgement
Session search

Access to Document

10.1007/978-3-319-76941-7_32

Cite this

Wang, P., Wang, T., Hou, Y., & Song, D. (2018). Modeling relevance judgement inspired by quantum weak measurement. In L. Azzopardi, G. Pasi, A. Hanbury, & B. Piwowarski (Eds.), Advances in Information Retrieval - 40th European Conference on IR Research, ECIR 2018, Proceedings (pp. 424-436). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10772 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-76941-7_32

Wang, Panpan ; Wang, Tianshu ; Hou, Yuexian et al. / Modeling relevance judgement inspired by quantum weak measurement. Advances in Information Retrieval - 40th European Conference on IR Research, ECIR 2018, Proceedings. editor / Leif Azzopardi ; Gabriella Pasi ; Allan Hanbury ; Benjamin Piwowarski. Springer Verlag, 2018. pp. 424-436 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{61aa1a804c7a46dbba653a22881ba93c,

title = "Modeling relevance judgement inspired by quantum weak measurement",

abstract = "Concept in Quantum theory (QT) has been successfully inspired analogous concepts in the field of Information Retrieval (IR). Many IR researchers have employed the QT to investigate cognitive phenomena within user behaviors, and also have verified the existence of quantum-like phenomena in real web search. However, for some complex search task, in which user{\textquoteright}s information need (IN) is dynamic and hard to be captured, QT currently adopted still can not explain some more complex cognitive phenomena. In this paper, a user experiment is conducted to investigate the variance of relevance judgement, and its results demonstrate that quantum Weak Measurement (WM) is more appropriate than the standard quantum measurement to model relevance judgement. Further, a WM-based session search model (WSM) is presented to model user{\textquoteright}s dynamic evolving IN. The extensive experiments are tested on the session track of TREC 2013 \& 2014 and verify the effectiveness of WSM.",

keywords = "Quantum weak measurement, Relevance judgement, Session search",

author = "Panpan Wang and Tianshu Wang and Yuexian Hou and Dawei Song",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 40th European Conference on Information Retrieval, ECIR 2018 ; Conference date: 26-03-2018 Through 29-03-2018",

year = "2018",

doi = "10.1007/978-3-319-76941-7\_32",

language = "English",

isbn = "9783319769400",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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}

Wang, P, Wang, T, Hou, Y & Song, D 2018, Modeling relevance judgement inspired by quantum weak measurement. in L Azzopardi, G Pasi, A Hanbury & B Piwowarski (eds), Advances in Information Retrieval - 40th European Conference on IR Research, ECIR 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10772 LNCS, Springer Verlag, pp. 424-436, 40th European Conference on Information Retrieval, ECIR 2018, Grenoble, France, 26/03/18. https://doi.org/10.1007/978-3-319-76941-7_32

Modeling relevance judgement inspired by quantum weak measurement. / Wang, Panpan; Wang, Tianshu; Hou, Yuexian et al.
Advances in Information Retrieval - 40th European Conference on IR Research, ECIR 2018, Proceedings. ed. / Leif Azzopardi; Gabriella Pasi; Allan Hanbury; Benjamin Piwowarski. Springer Verlag, 2018. p. 424-436 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10772 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Modeling relevance judgement inspired by quantum weak measurement

AU - Wang, Panpan

AU - Wang, Tianshu

AU - Hou, Yuexian

AU - Song, Dawei

N1 - Publisher Copyright: © Springer International Publishing AG, part of Springer Nature 2018.

PY - 2018

Y1 - 2018

N2 - Concept in Quantum theory (QT) has been successfully inspired analogous concepts in the field of Information Retrieval (IR). Many IR researchers have employed the QT to investigate cognitive phenomena within user behaviors, and also have verified the existence of quantum-like phenomena in real web search. However, for some complex search task, in which user’s information need (IN) is dynamic and hard to be captured, QT currently adopted still can not explain some more complex cognitive phenomena. In this paper, a user experiment is conducted to investigate the variance of relevance judgement, and its results demonstrate that quantum Weak Measurement (WM) is more appropriate than the standard quantum measurement to model relevance judgement. Further, a WM-based session search model (WSM) is presented to model user’s dynamic evolving IN. The extensive experiments are tested on the session track of TREC 2013 & 2014 and verify the effectiveness of WSM.

AB - Concept in Quantum theory (QT) has been successfully inspired analogous concepts in the field of Information Retrieval (IR). Many IR researchers have employed the QT to investigate cognitive phenomena within user behaviors, and also have verified the existence of quantum-like phenomena in real web search. However, for some complex search task, in which user’s information need (IN) is dynamic and hard to be captured, QT currently adopted still can not explain some more complex cognitive phenomena. In this paper, a user experiment is conducted to investigate the variance of relevance judgement, and its results demonstrate that quantum Weak Measurement (WM) is more appropriate than the standard quantum measurement to model relevance judgement. Further, a WM-based session search model (WSM) is presented to model user’s dynamic evolving IN. The extensive experiments are tested on the session track of TREC 2013 & 2014 and verify the effectiveness of WSM.

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DO - 10.1007/978-3-319-76941-7_32

M3 - Conference contribution

AN - SCOPUS:85044456675

SN - 9783319769400

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 424

EP - 436

BT - Advances in Information Retrieval - 40th European Conference on IR Research, ECIR 2018, Proceedings

A2 - Azzopardi, Leif

A2 - Pasi, Gabriella

A2 - Hanbury, Allan

A2 - Piwowarski, Benjamin

PB - Springer Verlag

T2 - 40th European Conference on Information Retrieval, ECIR 2018

Y2 - 26 March 2018 through 29 March 2018

ER -

Wang P, Wang T, Hou Y, Song D. Modeling relevance judgement inspired by quantum weak measurement. In Azzopardi L, Pasi G, Hanbury A, Piwowarski B, editors, Advances in Information Retrieval - 40th European Conference on IR Research, ECIR 2018, Proceedings. Springer Verlag. 2018. p. 424-436. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-76941-7_32

Modeling relevance judgement inspired by quantum weak measurement

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