TY - CHAP
T1 - A framework to automatically extract funding information from text
AU - Kayal, Subhradeep
AU - Afzal, Zubair
AU - Tsatsaronis, George
AU - Doornenbal, Marius
AU - Katrenko, Sophia
AU - Gregory, Michelle
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Many would argue that the currency of research is citations; however, researchers and funding organizations alike are lacking tools with which they can explore how this currency translates to funding opportunities. Motivated by this need, in this paper we address one of the fundamental problems facing the development of such a tool, namely the problem of automatically extracting funding information from scientific articles. For this purpose, we experiment with a two-stage framework which ingests text, filters paragraphs which contain funding information, and then combines sequential learning methods to detect named entities in a novel ensemble approach. We present a comparative analysis of each independent component of this pipeline, named FundingFinder, the results of which indicate that the said pipeline can extract the funding organizations and the associated grants, from scientific articles, accurately and efficiently.
AB - Many would argue that the currency of research is citations; however, researchers and funding organizations alike are lacking tools with which they can explore how this currency translates to funding opportunities. Motivated by this need, in this paper we address one of the fundamental problems facing the development of such a tool, namely the problem of automatically extracting funding information from scientific articles. For this purpose, we experiment with a two-stage framework which ingests text, filters paragraphs which contain funding information, and then combines sequential learning methods to detect named entities in a novel ensemble approach. We present a comparative analysis of each independent component of this pipeline, named FundingFinder, the results of which indicate that the said pipeline can extract the funding organizations and the associated grants, from scientific articles, accurately and efficiently.
UR - http://www.scopus.com/inward/record.url?scp=85063597199&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-13709-0_27
DO - 10.1007/978-3-030-13709-0_27
M3 - Chapter
AN - SCOPUS:85063597199
SN - 9783030137083
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 317
EP - 328
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Nicosia, Giuseppe
A2 - Giuffrida, Giovanni
A2 - Nicosia, Giuseppe
A2 - Pardalos, Panos
A2 - Sciacca, Vincenzo
A2 - Umeton, Renato
PB - Springer Verlag
Y2 - 13 September 2018 through 16 September 2018
ER -