Figure retrieval from collections of research articles

Saar Kuzi, Cheng Xiang Zhai

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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 languageEnglish (US)
Title of host publicationAdvances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings
EditorsLeif Azzopardi, Benno Stein, Claudia Hauff, Philipp Mayr, Djoerd Hiemstra, Norbert Fuhr
Number of pages15
ISBN (Print)9783030157111
StatePublished - 2019
Event41st European Conference on Information Retrieval, ECIR 2019 - Cologne, Germany
Duration: Apr 14 2019Apr 18 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11437 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference41st European Conference on Information Retrieval, ECIR 2019

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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