Figure retrieval from collections of research articles

Saar Kuzi; Cheng Xiang Zhai

doi:10.1007/978-3-030-15712-8_45

Figure retrieval from collections of research articles

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

Abstract

In this paper, we introduce and study a new task of figure retrieval in which the retrieval units are figures of research articles and the task is to rank figures with response to a query. As a first step toward addressing this task, we focus on textual queries and represent a figure using text extracted from its article. We suggest and study the effectiveness of several retrieval methods for the task. We build a test collection by using research articles from the ACL Anthology corpus and treating figure captions as queries. While having some limitations, using this data set we were able to obtain some interesting preliminary results on the relative effectiveness of different representations of a figure and different retrieval methods, which also shed some light regarding possible types of information need, and potential challenges in figure retrieval.

Original language	English (US)
Title of host publication	Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings
Editors	Leif Azzopardi, Benno Stein, Claudia Hauff, Philipp Mayr, Djoerd Hiemstra, Norbert Fuhr
Publisher	Springer
Pages	696-710
Number of pages	15
ISBN (Print)	9783030157111
DOIs	https://doi.org/10.1007/978-3-030-15712-8_45
State	Published - 2019
Event	41st European Conference on Information Retrieval, ECIR 2019 - Cologne, Germany Duration: Apr 14 2019 → Apr 18 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11437 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	41st European Conference on Information Retrieval, ECIR 2019
Country/Territory	Germany
City	Cologne
Period	4/14/19 → 4/18/19

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Online availability

10.1007/978-3-030-15712-8_45

Library availability

Discover UIUC Full Text

Cite this

Kuzi, S., & Zhai, C. X. (2019). Figure retrieval from collections of research articles. In L. Azzopardi, B. Stein, C. Hauff, P. Mayr, D. Hiemstra, & N. Fuhr (Eds.), Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings (pp. 696-710). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11437 LNCS). Springer. https://doi.org/10.1007/978-3-030-15712-8_45

Figure retrieval from collections of research articles. / Kuzi, Saar; Zhai, Cheng Xiang.
Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. ed. / Leif Azzopardi; Benno Stein; Claudia Hauff; Philipp Mayr; Djoerd Hiemstra; Norbert Fuhr. Springer, 2019. p. 696-710 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11437 LNCS).

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

Kuzi, S & Zhai, CX 2019, Figure retrieval from collections of research articles. in L Azzopardi, B Stein, C Hauff, P Mayr, D Hiemstra & N Fuhr (eds), Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11437 LNCS, Springer, pp. 696-710, 41st European Conference on Information Retrieval, ECIR 2019, Cologne, Germany, 4/14/19. https://doi.org/10.1007/978-3-030-15712-8_45

Kuzi S, Zhai CX. Figure retrieval from collections of research articles. In Azzopardi L, Stein B, Hauff C, Mayr P, Hiemstra D, Fuhr N, editors, Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. Springer. 2019. p. 696-710. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-15712-8_45

Kuzi, Saar ; Zhai, Cheng Xiang. / Figure retrieval from collections of research articles. Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. editor / Leif Azzopardi ; Benno Stein ; Claudia Hauff ; Philipp Mayr ; Djoerd Hiemstra ; Norbert Fuhr. Springer, 2019. pp. 696-710 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{954e832adf574733825b063a0079967e,

title = "Figure retrieval from collections of research articles",

abstract = "In this paper, we introduce and study a new task of figure retrieval in which the retrieval units are figures of research articles and the task is to rank figures with response to a query. As a first step toward addressing this task, we focus on textual queries and represent a figure using text extracted from its article. We suggest and study the effectiveness of several retrieval methods for the task. We build a test collection by using research articles from the ACL Anthology corpus and treating figure captions as queries. While having some limitations, using this data set we were able to obtain some interesting preliminary results on the relative effectiveness of different representations of a figure and different retrieval methods, which also shed some light regarding possible types of information need, and potential challenges in figure retrieval.",

author = "Saar Kuzi and Zhai, {Cheng Xiang}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 41st European Conference on Information Retrieval, ECIR 2019 ; Conference date: 14-04-2019 Through 18-04-2019",

year = "2019",

doi = "10.1007/978-3-030-15712-8_45",

language = "English (US)",

isbn = "9783030157111",

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

publisher = "Springer",

pages = "696--710",

editor = "Leif Azzopardi and Benno Stein and Claudia Hauff and Philipp Mayr and Djoerd Hiemstra and Norbert Fuhr",

booktitle = "Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings",

address = "Germany",

}

TY - GEN

T1 - Figure retrieval from collections of research articles

AU - Kuzi, Saar

AU - Zhai, Cheng Xiang

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - In this paper, we introduce and study a new task of figure retrieval in which the retrieval units are figures of research articles and the task is to rank figures with response to a query. As a first step toward addressing this task, we focus on textual queries and represent a figure using text extracted from its article. We suggest and study the effectiveness of several retrieval methods for the task. We build a test collection by using research articles from the ACL Anthology corpus and treating figure captions as queries. While having some limitations, using this data set we were able to obtain some interesting preliminary results on the relative effectiveness of different representations of a figure and different retrieval methods, which also shed some light regarding possible types of information need, and potential challenges in figure retrieval.

AB - In this paper, we introduce and study a new task of figure retrieval in which the retrieval units are figures of research articles and the task is to rank figures with response to a query. As a first step toward addressing this task, we focus on textual queries and represent a figure using text extracted from its article. We suggest and study the effectiveness of several retrieval methods for the task. We build a test collection by using research articles from the ACL Anthology corpus and treating figure captions as queries. While having some limitations, using this data set we were able to obtain some interesting preliminary results on the relative effectiveness of different representations of a figure and different retrieval methods, which also shed some light regarding possible types of information need, and potential challenges in figure retrieval.

UR - http://www.scopus.com/inward/record.url?scp=85064857280&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85064857280&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-15712-8_45

DO - 10.1007/978-3-030-15712-8_45

M3 - Conference contribution

AN - SCOPUS:85064857280

SN - 9783030157111

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

SP - 696

EP - 710

BT - Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings

A2 - Azzopardi, Leif

A2 - Stein, Benno

A2 - Hauff, Claudia

A2 - Mayr, Philipp

A2 - Hiemstra, Djoerd

A2 - Fuhr, Norbert

PB - Springer

T2 - 41st European Conference on Information Retrieval, ECIR 2019

Y2 - 14 April 2019 through 18 April 2019

ER -

Figure retrieval from collections of research articles

Abstract

Publication series

Conference

ASJC Scopus subject areas

Online availability

Library availability

Related links

Fingerprint

Cite this