TY - GEN
T1 - Overview of ChEMU 2022 Evaluation Campaign
T2 - 13th International Conference of the Cross-Language Evaluation Forum for European Languages, CLEF 2022
AU - Li, Yuan
AU - Fang, Biaoyan
AU - He, Jiayuan
AU - Yoshikawa, Hiyori
AU - Akhondi, Saber A.
AU - Druckenbrodt, Christian
AU - Thorne, Camilo
AU - Afzal, Zubair
AU - Zhai, Zenan
AU - Baldwin, Timothy
AU - Verspoor, Karin
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - In this paper, we provide an overview of the Cheminformatics Elsevier Melbourne University (ChEMU) evaluation lab 2022, part of the Conference and Labs of the Evaluation Forum 2022 (CLEF 2022). The ChEMU campaign focuses on information extraction tasks over chemical reactions in patents. The ChEMU 2020 lab provided two information extraction tasks, named entity recognition and event extraction. The ChEMU 2021 lab introduced one more task, anaphora resolution. This year, we re-run all the three tasks with new test data. Together, the tasks support comprehensive automatic chemical patent analysis. Herein, we describe the resources created for these tasks and the evaluation methodology adopted. We also provide a brief summary of the methods employed by participants of this lab and the results obtained across 22 runs from 3 teams, finding that several submissions achieve better results than the baseline methods prepared by the organizers.
AB - In this paper, we provide an overview of the Cheminformatics Elsevier Melbourne University (ChEMU) evaluation lab 2022, part of the Conference and Labs of the Evaluation Forum 2022 (CLEF 2022). The ChEMU campaign focuses on information extraction tasks over chemical reactions in patents. The ChEMU 2020 lab provided two information extraction tasks, named entity recognition and event extraction. The ChEMU 2021 lab introduced one more task, anaphora resolution. This year, we re-run all the three tasks with new test data. Together, the tasks support comprehensive automatic chemical patent analysis. Herein, we describe the resources created for these tasks and the evaluation methodology adopted. We also provide a brief summary of the methods employed by participants of this lab and the results obtained across 22 runs from 3 teams, finding that several submissions achieve better results than the baseline methods prepared by the organizers.
KW - Chemical patents
KW - Information Extraction
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=85137979420&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-13643-6_30
DO - 10.1007/978-3-031-13643-6_30
M3 - Contribución a la conferencia
AN - SCOPUS:85137979420
SN - 9783031136429
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 521
EP - 540
BT - Experimental IR Meets Multilinguality, Multimodality, and Interaction - 13th International Conference of the CLEF Association, CLEF 2022, Proceedings
A2 - Barrón-Cedeño, Alberto
A2 - Da San Martino, Giovanni
A2 - Faggioli, Guglielmo
A2 - Ferro, Nicola
A2 - Degli Esposti, Mirko
A2 - Sebastiani, Fabrizio
A2 - Macdonald, Craig
A2 - Pasi, Gabriella
A2 - Hanbury, Allan
A2 - Potthast, Martin
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 5 September 2022 through 8 September 2022
ER -