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An editorial note on extraction and evaluation of knowledge entities from scientific documents

Author

Listed:
  • Chengzhi Zhang

    (Nanjing University of Science and Technology)

  • Philipp Mayr

    (GESIS-Leibniz Institute for the Social Sciences)

  • Wei Lu

    (Wuhan University)

  • Yi Zhang

    (University of Technology Sydney)

Abstract

No abstract is available for this item.

Suggested Citation

  • Chengzhi Zhang & Philipp Mayr & Wei Lu & Yi Zhang, 2024. "An editorial note on extraction and evaluation of knowledge entities from scientific documents," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7169-7174, November.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:11:d:10.1007_s11192-024-05166-1
    DOI: 10.1007/s11192-024-05166-1
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    References listed on IDEAS

    as
    1. John Dagdelen & Alexander Dunn & Sanghoon Lee & Nicholas Walker & Andrew S. Rosen & Gerbrand Ceder & Kristin A. Persson & Anubhav Jain, 2024. "Structured information extraction from scientific text with large language models," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Zhongyi Wang & Jing Chen & Jiangping Chen & Haihua Chen, 2024. "Identifying interdisciplinary topics and their evolution based on BERTopic," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7359-7384, November.
    3. Nina Smirnova & Philipp Mayr, 2024. "Embedding models for supervised automatic extraction and classification of named entities in scientific acknowledgements," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7261-7285, November.
    4. Tingting Wei & Danyu Feng & Shiling Song & Cai Zhang, 2024. "An extraction and novelty evaluation framework for technology knowledge elements of patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7417-7442, November.
    5. Yujie Zhang & Rujiang Bai & Ling Kong & Xiaoyue Wang, 2024. "2SCE-4SL: a 2-stage causality extraction framework for scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7175-7195, November.
    6. Wang, Yuzhuo & Xiang, Yi & Zhang, Chengzhi, 2024. "Exploring motivations for algorithm mention in the domain of natural language processing: A deep learning approach," Journal of Informetrics, Elsevier, vol. 18(4).
    7. Dongin Nam & Jiwon Kim & Jeeyoung Yoon & Chaemin Song & Seongdeok Kim & Min Song, 2024. "Examining knowledge entities and its relationships based on citation sentences using a multi-anchor bipartite network," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7197-7228, November.
    8. Junsheng Zhang & Xiaoping Sun & Zhihui Liu, 2024. "Measuring the evolving stage of temporal distribution of research topic keyword in scientific literature by research heat curve," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7287-7328, November.
    9. Mengjia Wu & Yi Zhang & Mark Markley & Caitlin Cassidy & Nils Newman & Alan Porter, 2024. "COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7229-7259, November.
    10. Chao Yu & Chuhan Wang & Tongyang Zhang & Yi Bu & Jian Xu, 2024. "Analyzing research diversity of scholars based on multi-dimensional calculation of knowledge entities," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7329-7358, November.
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