TY - JOUR
T1 - Overview of the Third Workshop on Scholarly Document Processing
AU - Cohan, Arman
AU - Feigenblat, Guy
AU - Freitag, Dayne
AU - Ghosal, Tirthankar
AU - Herrmannova, Drahomira
AU - Knoth, Petr
AU - Lo, Kyle
AU - Mayr, Philipp
AU - Shmueli-Scheuer, Michal
AU - de Waard, Anita
AU - Wang, Lucy Lu
N1 - Publisher Copyright:
© 2022 COLING. All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - With the ever-increasing pace of research and high volume of scholarly communication, scholars face a daunting task. Not only must they keep up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. These needs have motivated an increasing focus on computational methods for enhancing search, summarization, and analysis of scholarly documents. However, the various strands of research on scholarly document processing remain fragmented. To reach out to the broader NLP and AI/ML community, pool distributed efforts in this area, and enable shared access to published research, we held the 3rd Workshop on Scholarly Document Processing (SDP) at COLING as a hybrid event (https://sdproc.org/2022/). The SDP workshop consisted of a research track, three invited talks and five Shared Tasks: 1) MSLR22: Multi-Document Summarization for Literature Reviews, 2) DAGPap22: Detecting automatically generated scientific papers, 3) SV-Ident 2022: Survey Variable Identification in Social Science Publications, 4) SKGG: Scholarly Knowledge Graph Generation, 5) MuP 2022: Multi Perspective Scientific Document Summarization. The program was geared towards NLP, information retrieval, and data mining for scholarly documents, with an emphasis on identifying and providing solutions to open challenges.
AB - With the ever-increasing pace of research and high volume of scholarly communication, scholars face a daunting task. Not only must they keep up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. These needs have motivated an increasing focus on computational methods for enhancing search, summarization, and analysis of scholarly documents. However, the various strands of research on scholarly document processing remain fragmented. To reach out to the broader NLP and AI/ML community, pool distributed efforts in this area, and enable shared access to published research, we held the 3rd Workshop on Scholarly Document Processing (SDP) at COLING as a hybrid event (https://sdproc.org/2022/). The SDP workshop consisted of a research track, three invited talks and five Shared Tasks: 1) MSLR22: Multi-Document Summarization for Literature Reviews, 2) DAGPap22: Detecting automatically generated scientific papers, 3) SV-Ident 2022: Survey Variable Identification in Social Science Publications, 4) SKGG: Scholarly Knowledge Graph Generation, 5) MuP 2022: Multi Perspective Scientific Document Summarization. The program was geared towards NLP, information retrieval, and data mining for scholarly documents, with an emphasis on identifying and providing solutions to open challenges.
UR - http://www.scopus.com/inward/record.url?scp=85150206968&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85150206968
SN - 2951-2093
VL - 29
SP - 1
EP - 6
JO - Proceedings - International Conference on Computational Linguistics, COLING
JF - Proceedings - International Conference on Computational Linguistics, COLING
IS - 9
T2 - 3rd Workshop on Scholarly Document Processing, SDP 2022 at 29th International Conference on Computational Linguistics, COLING 2022
Y2 - 12 October 2022 through 17 October 2022
ER -