An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications

Lianghong Lin; Wenxiu Xie; Zili Chen; Tianyong Hao

doi:10.18653/v1/2024.sdp-1.11

An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications

Lianghong Lin
, Wenxiu Xie
, Zili Chen
, Tianyong Hao

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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Abstract

Author affiliation information plays a key role in bibliometric analyses and is essential for evaluating studies. However, as author affiliation information has not been standardized, which leads to difficulties such as synonym ambiguity and incomplete data during automated processing. To address the challenge, this paper proposes an end-to-end entity recognition and disambiguation framework for identifying author affiliation from literature publications. For entity disambiguation, an algorithm combining word embedding and spatial embedding is presented considering that author affiliation texts often contain rich geographic information. The disambiguation algorithm utilizes the semantic information and geographic information, which effectively enhances entity recognition and disambiguation effect. In addition, the proposed framework facilitates the effective utilization of the extensive literature in the PubMed database for comprehensive bibliometric analysis. The experimental results verify the robustness and effectiveness of the algorithm. © 2024 Association for Computational Linguistics.

Original language	English
Title of host publication	Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024)
Editors	Tirthankar Ghosal, Amanpreet Singh, Anita Waard, Philipp Mayr, Aakanksha Naik, Orion Weller, Yoonjoo Lee, Shannon Shen, Yanxia Qin
Publisher	Association for Computational Linguistics
Pages	120-129
ISBN (Print)	979-8-89176-151-3
DOIs	https://doi.org/10.18653/v1/2024.sdp-1.11
Publication status	Published - Aug 2024
Event	Fourth Workshop on Scholarly Document Processing at ACL 2024 - Bangkok, Thailand Duration: 16 Aug 2024 → 16 Aug 2024 https://aclanthology.org/2024.sdp-1 https://sdproc.org/2024/index.html

Publication series

Name	SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop

Conference

Conference	Fourth Workshop on Scholarly Document Processing at ACL 2024
Place	Thailand
City	Bangkok
Period	16/08/24 → 16/08/24
Internet address	https://aclanthology.org/2024.sdp-1 https://sdproc.org/2024/index.html

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This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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10.18653/v1/2024.sdp-1.11

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Lin, L., Xie, W., Chen, Z., & Hao, T. (2024). An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications. In T. Ghosal, A. Singh, A. Waard, P. Mayr, A. Naik, O. Weller, Y. Lee, S. Shen, & Y. Qin (Eds.), Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024) (pp. 120-129). (SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.sdp-1.11

Lin, Lianghong ; Xie, Wenxiu ; Chen, Zili et al. / An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications. Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024). editor / Tirthankar Ghosal ; Amanpreet Singh ; Anita Waard ; Philipp Mayr ; Aakanksha Naik ; Orion Weller ; Yoonjoo Lee ; Shannon Shen ; Yanxia Qin. Association for Computational Linguistics, 2024. pp. 120-129 (SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop).

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title = "An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications",

abstract = "Author affiliation information plays a key role in bibliometric analyses and is essential for evaluating studies. However, as author affiliation information has not been standardized, which leads to difficulties such as synonym ambiguity and incomplete data during automated processing. To address the challenge, this paper proposes an end-to-end entity recognition and disambiguation framework for identifying author affiliation from literature publications. For entity disambiguation, an algorithm combining word embedding and spatial embedding is presented considering that author affiliation texts often contain rich geographic information. The disambiguation algorithm utilizes the semantic information and geographic information, which effectively enhances entity recognition and disambiguation effect. In addition, the proposed framework facilitates the effective utilization of the extensive literature in the PubMed database for comprehensive bibliometric analysis. The experimental results verify the robustness and effectiveness of the algorithm. {\textcopyright} 2024 Association for Computational Linguistics.",

author = "Lianghong Lin and Wenxiu Xie and Zili Chen and Tianyong Hao",

year = "2024",

month = aug,

doi = "10.18653/v1/2024.sdp-1.11",

language = "English",

isbn = "979-8-89176-151-3",

series = "SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop",

publisher = "Association for Computational Linguistics",

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editor = "Tirthankar Ghosal and Amanpreet Singh and Anita Waard and Philipp Mayr and Aakanksha Naik and Orion Weller and Yoonjoo Lee and Shannon Shen and Yanxia Qin",

booktitle = "Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024)",

address = "United States",

note = "Fourth Workshop on Scholarly Document Processing at ACL 2024 ; Conference date: 16-08-2024 Through 16-08-2024",

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Lin, L, Xie, W, Chen, Z & Hao, T 2024, An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications. in T Ghosal, A Singh, A Waard, P Mayr, A Naik, O Weller, Y Lee, S Shen & Y Qin (eds), Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024). SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop, Association for Computational Linguistics, pp. 120-129, Fourth Workshop on Scholarly Document Processing at ACL 2024, Bangkok, Thailand, 16/08/24. https://doi.org/10.18653/v1/2024.sdp-1.11

An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications. / Lin, Lianghong; Xie, Wenxiu; Chen, Zili et al.
Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024). ed. / Tirthankar Ghosal; Amanpreet Singh; Anita Waard; Philipp Mayr; Aakanksha Naik; Orion Weller; Yoonjoo Lee; Shannon Shen; Yanxia Qin. Association for Computational Linguistics, 2024. p. 120-129 (SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T1 - An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications

AU - Lin, Lianghong

AU - Xie, Wenxiu

AU - Chen, Zili

AU - Hao, Tianyong

PY - 2024/8

Y1 - 2024/8

N2 - Author affiliation information plays a key role in bibliometric analyses and is essential for evaluating studies. However, as author affiliation information has not been standardized, which leads to difficulties such as synonym ambiguity and incomplete data during automated processing. To address the challenge, this paper proposes an end-to-end entity recognition and disambiguation framework for identifying author affiliation from literature publications. For entity disambiguation, an algorithm combining word embedding and spatial embedding is presented considering that author affiliation texts often contain rich geographic information. The disambiguation algorithm utilizes the semantic information and geographic information, which effectively enhances entity recognition and disambiguation effect. In addition, the proposed framework facilitates the effective utilization of the extensive literature in the PubMed database for comprehensive bibliometric analysis. The experimental results verify the robustness and effectiveness of the algorithm. © 2024 Association for Computational Linguistics.

AB - Author affiliation information plays a key role in bibliometric analyses and is essential for evaluating studies. However, as author affiliation information has not been standardized, which leads to difficulties such as synonym ambiguity and incomplete data during automated processing. To address the challenge, this paper proposes an end-to-end entity recognition and disambiguation framework for identifying author affiliation from literature publications. For entity disambiguation, an algorithm combining word embedding and spatial embedding is presented considering that author affiliation texts often contain rich geographic information. The disambiguation algorithm utilizes the semantic information and geographic information, which effectively enhances entity recognition and disambiguation effect. In addition, the proposed framework facilitates the effective utilization of the extensive literature in the PubMed database for comprehensive bibliometric analysis. The experimental results verify the robustness and effectiveness of the algorithm. © 2024 Association for Computational Linguistics.

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M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 979-8-89176-151-3

T3 - SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop

SP - 120

EP - 129

BT - Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024)

A2 - Ghosal, Tirthankar

A2 - Singh, Amanpreet

A2 - Waard, Anita

A2 - Mayr, Philipp

A2 - Naik, Aakanksha

A2 - Weller, Orion

A2 - Lee, Yoonjoo

A2 - Shen, Shannon

A2 - Qin, Yanxia

PB - Association for Computational Linguistics

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Y2 - 16 August 2024 through 16 August 2024

ER -

Lin L, Xie W, Chen Z, Hao T. An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications. In Ghosal T, Singh A, Waard A, Mayr P, Naik A, Weller O, Lee Y, Shen S, Qin Y, editors, Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024). Association for Computational Linguistics. 2024. p. 120-129. (SDP - Workshop on Scholarly Document Processing, Proceedings of the Workshop). doi: 10.18653/v1/2024.sdp-1.11

An end-to-end entity recognition and disambiguation framework for identifying Author Affiliation from literature publications

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