2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2021)

at the ACM/IEEE Joint Conference on Digital Libraries 2021 (JCDL2021), Online

Call for Papers

You are invited to participate in the 2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2021), to be held as part of the ACM/IEEE Joint Conference on Digital Libraries 2021, September 27-30, 2021, Online (Due to the Global Pandemic)

https://eeke-workshop.github.io/2021

Aim of the Workshop

In the era of big data, massive amounts of   information and data have   dramatically changed human civilization. The broad availability  of   information provides more opportunities for people, but there has   appeared a  new challenge: how can we obtain useful knowledge from   numerous information sources. A  knowledge entity is a relatively independent and integral   knowledge module in a special discipline or a research domain [1]. As a   crucial medium for knowledge transmission, scientific documents that   contain a large number of  knowledge entities attract the attention of   scholars [2]. In  scientific documents, knowledge entities refer to the   knowledge mentioned or  cited by authors, such as algorithms, models,   theories, datasets and software,  which reflect the various resources   used by the authors in solving problems.  Extracting knowledge entities   from scientific documents in an accurate and  comprehensive way becomes a   significant topic. We may recommend documents  related to a given   knowledge entity (e.g. LSTM model) for scholars, especially for     beginners in a research field. DARPA has recently launched the ASKE   (Automating  Scientific Knowledge Extraction) project [3], which aims to   develop  next-generation applications of artificial intelligence.
         Therefore,  the goal of this workshop is to engage the related   communities in open problems  in the extraction and evaluation of   knowledge entities from scientific  documents.  At present, scholars have used knowledge  entities to construct general   knowledge-graphs [4] and domain knowledge-graphs [5].  Data sources for   these studies include text (news, policy files, email, etc.)  and   multimedia (video, image, etc.) data. Compared to existing research and    workshops like Joint workshop on Bibliometric-enhanced Information   Retrieval  and Natural Language Processing for Digital Libraries   (BIRNDL) [6] or   Workshop on Mining Scientific Publications (WOSP) [7],   this workshop aims to  extract knowledge entities from scientific   documents, and explore the feature  of entities to conduct practical   applications. The results of this workshop are  expected to provide   scholars, especially early career researchers, with  knowledge   recommendations and other knowledge entity-based services.

Workshop Topics

This      workshop will be relevant to scholars in computer and information     science,  specialized in Information Extraction, Text Mining, NLP, IR     and Digital  Libraries. It will also be of importance for all     stakeholders in the  publication pipeline: implementers, publishers and     policymakers.    This workshop entitles this cutting-edge and  cross-disciplinary direction Extraction  and Evaluation of Knowledge Entity,    highlighting the development of  intelligent methods for identifying     knowledge claims in scientific documents,  and promoting the application    of knowledge entities. We invite stimulating  research on topics     including, but not limited to, methods of knowledge entity   extraction     and applications of knowledge entity. Specific examples of fields of    interest include:

• Extraction knowlege and entity from scientific documents

• Model  and algorithmize entity extraction from scientific documents

• Dataset  and metrics mention extraction from scientific documents

• Software  and tool extraction from scientific documents [8]

• Construction  of a knowledge entity graph and roadmap [9]

• Knowledge  entity summarization

• Relation  extraction of knowledge entity

• Construction  of a knowledge base of knowledge entities

• Bibliometrics  of knowledge entity

• Evaluation of knowledge entity in the scientific documents

• Application  of knowledge entity extraction

Programme

TBD

(The  workshop will last two half-days and specific   activities     include keynotes, paper presentations and a poster & demonstration session.)

Submission Information

Regular papers: All submissions must be written in English, following the ACM Proceedings template (10 pages for full papers and 4 pages for short papers exclusive of unlimited pages for references) and should be submitted as PDF files to EasyChair.

Poster & demonstration: We welcome submissions     detailing original, early findings, works in progress and industrial     applications of knowledge entities extraction ande evaluation for a     special poster session, possibly with a 2-minute presentation in the     main session. Some research track papers will also be invited to the     poster track instead, although there will be no difference in the final     proceedings between poster and research track submissions. These   papers   should follow the same format as the research track papers but   can be   shorter (2 pages for poster and demo papers).

Submit a paper

All submissions will be reviewed by at least two independent  reviewers. Please   be aware of the fact that at least   one author per paper needs to   register for the workshop and   attend the workshop to present the work. In case of no-show   the paper (even if accepted) will be deleted from the   proceedings and from the program.

Workshop proceedings will be deposited online in the CEUR workshop     proceedings publication service. This way the  proceedings will be   permanently available and citable (digital   persistent identifiers and   long term preservation).

Special Issue

Accepted submissions will be invited to submit to our special issue in Scientometrics or Journal of Informetrics.

Important Dates

All dates are Anywhere on Earth (AoE).

Deadline for submission: August, 10, 2021
         Notification of acceptance: September 10, 2021
         Camera ready: September 20, 2021
         Workshop: September 27-30, 2021

Main Organising Committee

Chengzhi Zhang (zhangcz@njust.edu.cn)   is a professor of Department of Information Management, Nanjing   University of  Science and Technology, China. He received his PhD degree   of Information Science from Nanjing University, China. He has published   more than 100  publications, including JASIST, Aslib JIM, JOI, OIR,   SCIM, ACL, NAACL, etc. His current research interests include scientific   text mining, knowledge entity extraction and evaluation, social media   mining. He serves as Editorial Board Member and Managing Guest Editor   for 10 international journals (Patterns, OIR, TEL, IDD, NLE, JDIS, DIM,   DI, etc.) and PC members of several international conferences in fields   of natural language process and scientometrics. (https://chengzhizhang.github.io/)

Philipp Mayr ( philipp.mayr@gesis.org)   is a  team leader at the GESIS - Leibniz-Institute for the Social     Sciences  department Knowledge Technologies for the Social Sciences   (WTS). He received  his PhD in applied informetrics and information     retrieval from the Berlin  School of Library and Information Science at  Humboldt University Berlin. He has  published in top conferences and     prestigious journals in the areas  informetrics, information retrieval   and digital libraries. His research group  focuses on methods and     techniques for interactive information retrieval and   data set search.     He was the main organizer of the BIR workshops at ECIR 2014-2021  and  the BIRNDL workshops at JCDL 2016 and SIGIR 2017-2019. (https://philippmayr.github.io/)

Wei  Lu (weilu@whu.edu.cn) is a professor of  School of Information Management and director of   Information Retrieval and  Knowledge Mining Center, Wuhan University. He received his PhD   degree of Information Science from  Wuhan University, China. His current   research interests include information retrieval, text mining, QA etc.   He has papers published on SIGIR, Information  Sciences, JASIT, Journal   of Information Science etc. He serves as diverse roles  (e.g.,   Associate Editor, Editorial Board Member, and Managing Guest Editor) for    several journals. (http://39.103.203.133/member/4)

Yi Zhang (yi.zhang@uts.edu.au) works as a Senior Lecturer at the Australian Artificial Intelligence Institute, University of Technology Sydney. He holds dual Ph.D. degrees in Management Science & Engineering and in Software Engineering. His research interests align with intelligent bibliometrics - incorporating artificial intelligence and data science techniques with bibliometric indicators for broad science, technology & innovation studies. He is the recipient of the 2019 Discovery Early Career Researcher Award granted by the Australian Research Council. He serves as the Associate Editor for Technol. Forecast. & Soc. Change, the Editorial Board Member for the IEEE Trans. Eng. Manage., and the Advisory Board Member for the International Center for the Study of Research.. (https://www.uts.edu.au/staff/yi.zhang)

Programme Committee

• Alireza Abbasi, University of New South Wales (Canberra)
  

• Katarina Boland, GESIS - Leibniz Institute for the Social Sciences
  

• Chong Chen, Beijing Normal University
  

• Haihua Chen, University of North Texas
  

• Gong Cheng, Nanjing University
  

• Jian Du, Peking University
  

• Edward Fox, Virgina Tech
  

• Saeed-Ul Hassan, Information Technology University
  

• Jiangen He, The University of Tennessee

• Zhigang Hu, Dalian University of Technology
  

• Bolin Hua, Peking University
  

• Chenliang Li, Wuhan Univerisity
  

• Kai Li, Renmin University of China
  

• Shutian Ma, Tencent
  

• Jin Mao, Wuhan Univerisity
  

• Wolfgang Otto, GESIS - Leibniz-Institute for the Social Sciences
  

• Xuelian Pan, Nanjing  University
  

• Dwaipayan Roy, GESIS - Leibniz-Institute for the Social Sciences
  

• Mayank Singh, Indian Institute of Technology Gandhinagar
  

• Arho Suominen, VTT Technical Research Centre of Finland
  

• Suppawong Tuarob, Mahidol University
  

• Dongbo Wang, Nanjing Argricultural University
  

• Xuefeng Wang, Beijing Institute of Technology

• Yuzhuo Wang, Nanjing University of Science and Technology
  

• Jian Wu, Old Dominion University
  

• Mengjia Wu, University of Technology Sydney
  

• Tianxing Wu, Southeast University
  

• Yanghua Xiao, Fudan University
  

• Jian Xu, Sun Yat-sen university
  

• Shuo Xu, Beijing University of Technology
  

• Erjia Yan, Drexel University
  

• Heng Zhang, Nanjing University of Science and Technology
  

• Jinzhu Zhang, Nanjing University of Science and Technology
  

• Xiaojuan Zhang, Southwest University
  

• Yingyi Zhang, Nanjing University of Science and Technology
  

• Zhixiong Zhang, National Science Library, Chinese Academy of Sciences
  

• Yongjun Zhu, Sungkyunkwan University

References

1. Chang, X., & Zheng, Q. (2007). Knowledge element   extraction for knowledge-based learning resources organization. In   International Conference on Web-Based Learning (pp. 102-113). Springer,  Berlin, Heidelberg.

2. Ying, D., Min, S., Jia, H., Qi,  Y., Erjia, Y., Lili, L., Tamy, C.      Entitymetrics: Measuring the Impact of  Entities. Plos One, 2013, 8(8),      e71416.

3. https://www.darpa.mil/program/automating-scientific-knowledge-extraction

4. Auer, S., Bizer, C., Kobilarov, G., Lehmann, J.,   Cyganiak, R., & Ives, Z. (2007). Dbpedia: A nucleus for a web of   open data. In The semantic web (pp. 722-735). Springer, Berlin,   Heidelberg.

5. http://www.geonames.org/

6. Cabanac, G., Chandrasekaran, M. K., Frommholz, I.,   Jaidka, K., Kan, M. Y., Mayr, P., & Wolfram, D. (2017). Report on   the Joint Workshop on Bibliometric-enhanced Information Retrieval and   Natural Language Processing for Digital Libraries (BIRNDL 2016). In ACM  SIGIR Forum (Vol. 50, No. 2, pp. 36-43). New York, NY, USA: ACM.

7. https://wosp.core.ac.uk/lrec2018/

8. Boland, K., & Krüger, F. (2019). Distant supervision for       silver  label generation of software mentions in social scientific       publications. In Proceedings of the 4th Joint Workshop on        Bibliometric-enhanced Information Retrieval and Natural Language       Processing for  Digital Libraries(pp. 15-27).

9. Zha, H., Chen, W., Li, K., & Yan, X. (2019).   Mining Algorithm Roadmap in Scientific Publications. In Proceedings of   the 25th ACM SIGKDD International Conference on Knowledge Discovery   & Data Mining (pp. 1083-1092).

Links

Related  Workshops：
       

Related  Workshops：
       BIRNDL  2019：The 4th Joint Workshop on Bibliometric-enhanced Information Retrieval  and Natural Language Processing for Digital Libraries
       Venue: SIGIR 2019 in Paris, France
       Proceedings: http://ceur-ws.org/Vol-2414/ 

SDP 2020：First Workshop on Scholarly Document Processing
       Venue: 2020 Conference on Empirical Methods in Natural LanguageProcessing (EMNLP 2020)
       Website: https://ornlcda.github.io/SDProc/ 

EEKE 2020：First Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents
       Venue: ACM/IEEE Joint Conference on Digital Libraries 2020 (JCDL2020)
       Website: https://eeke2020.github.io/

AII 2021：First Workshop on AI + Informetrics (AII2021)
       Venue:  iConference2021
       Website: https://ai-informetrics.github.io/