Research article Special Issues

Advancing document-level event extraction: Integration across texts and reciprocal feedback

  • Received: 17 August 2023 Revised: 16 October 2023 Accepted: 22 October 2023 Published: 03 November 2023
  • The primary objective of document-level event extraction is to extract relevant event information from lengthy texts. However, many existing methods for document-level event extraction fail to fully incorporate the contextual information that spans across sentences. To overcome this limitation, the present study proposes a document-level event extraction model called Integration Across Texts and Reciprocal Feedback (IATRF). The proposed model constructs a heterogeneous graph and employs a graph convolutional network to enhance the connection between document and entity information. This approach facilitates the acquisition of semantic information enriched with document-level context. Additionally, a Transformer classifier is introduced to transform multiple event types into a multi-label classification task. To tackle the challenge of event argument recognition, this paper introduces the Reciprocal Feedback Argument Extraction strategy. Experimental results conducted on both our COSM dataset and the publicly available ChFinAnn dataset demonstrate that the proposed model outperforms previous methods in terms of F1 value, thus confirming its effectiveness. The IATRF model effectively solves the problems of long-distance document context-aware representation and cross-sentence argument dispersion.

    Citation: Min Zuo, Jiaqi Li, Di Wu, Yingjun Wang, Wei Dong, Jianlei Kong, Kang Hu. Advancing document-level event extraction: Integration across texts and reciprocal feedback[J]. Mathematical Biosciences and Engineering, 2023, 20(11): 20050-20072. doi: 10.3934/mbe.2023888

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  • The primary objective of document-level event extraction is to extract relevant event information from lengthy texts. However, many existing methods for document-level event extraction fail to fully incorporate the contextual information that spans across sentences. To overcome this limitation, the present study proposes a document-level event extraction model called Integration Across Texts and Reciprocal Feedback (IATRF). The proposed model constructs a heterogeneous graph and employs a graph convolutional network to enhance the connection between document and entity information. This approach facilitates the acquisition of semantic information enriched with document-level context. Additionally, a Transformer classifier is introduced to transform multiple event types into a multi-label classification task. To tackle the challenge of event argument recognition, this paper introduces the Reciprocal Feedback Argument Extraction strategy. Experimental results conducted on both our COSM dataset and the publicly available ChFinAnn dataset demonstrate that the proposed model outperforms previous methods in terms of F1 value, thus confirming its effectiveness. The IATRF model effectively solves the problems of long-distance document context-aware representation and cross-sentence argument dispersion.



    AIMS Microbiology is an international Open Access journal devoted to publishing peer-reviewed, high quality, original papers in the field of microbiology. Together with the Editorial Office of AIMS Microbiology, I wish to testify my sincere gratitude to all authors, members of the editorial board and reviewers for their contribution to AIMS Microbiology in 2022.

    In 2022, We received more than 200 manuscripts and 40 of them were accepted and published. These published papers include 23 research articles, 11 review articles, 2 editorials, 2 communications and 1 brief report papers. The authors of the manuscripts are from more than 20 countries. The data shows a significant increase of international collaborations on the research of microbiology.

    An important part of our strategy has been preparation of special issues. 2 special issues published more than five papers. AIMS Microbiology have invited 17 experts to join our Editorial Board in 2022. We will continue to renew Editorial Board in 2022.

    We hope that in 2023, AIMS Microbiology can receive and collect more excellent articles to be able to publish. The journal will dedicate to publishing high quality papers by regular issues as well as special issues organized by the members of the editorial board. We believe that all these efforts will increase the impact and citations of the papers published by AIMS Microbiology.

    On behalf of

    AIMS Microbiology Editorial Board

    The submissions of our AIMS Microbiology journal in 2022 increased. In 2022, AIMS Microbiology published 4 issues, a total of 40 articles were published online, and the category of published articles is as follows:

    Type Number
    Research 23
    Review 11
    Editorial 2
    Communication 2
    Brief report 1

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    Peer Review Rejection rate: 49%

    Publication time (from submission to online): 75 days

    Organizing high-quality special issue is a very important work in 2022. In 2022, 7 special issues were called. Listed below are some examples of issues that have more than 5 papers. We encourage Editorial Board members to propose more potential topics, and to act as editors of special issues.

    Special issue link Papers
    Biotechnological applications of microorganisms in Industry, Agriculture and Environment https://www.aimspress.com/aimsmicro/article/6262/special-articles 8
    Antimicrobials and Resistance https://www.aimspress.com/aimsmicro/article/6209/special-articles 5

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    AIMS Microbiology has Editorial Board members representing researchers from 20 countries, which are shown below. We are constantly assembling the editorial board to be representative to a variety of disciplines across the field of microbiology. AIMS Microbiology has 81 members now, and 17 of them joined in 2022. We will continue to invite dedicated experts and researchers in order to renew the Editorial Board in 2022.

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    In the recent two years, our journal has developed much faster than before; Our journal has been indexed in Web of Science, Scopus and PubMed databases. We received more than 200 manuscript submissions and published 40 papers in 2022. We have added 17 new Editorial Board members.

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