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Reference Metadata Extraction from Korean Research Papers

  • Jae-Wook Seol
  • Won-Jun Choi
  • Hee-Seok Jeong
  • Hye-Kyong Hwang
  • Hwa-Mook YoonEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11308)

Abstract

A large amount of research papers are published in various fields and the ability to accurately extract metadata from a list of references is becoming increasingly important. Moreover, metadata extraction is crucial for measuring the influence of a particular study or researcher. However, it is difficult to automatically extract data from most lists of references because they consist of unstructured strings with bibliographies structured in various formats depending on the proceedings. Thus, this paper presents an effective and accurate method for extracting metadata, such as author name, title, publication year, volume, issue, page numbers, and journal name from heterogeneous references using the conditional random fields model. To conduct an experiment measuring the effectiveness of the proposed model, 1,415 references from 93 different academic papers published in Korea were used and a high accuracy of 97.10% was obtained.

Keywords

Reference extraction Metadata extraction Conditional random fields 

Notes

Acknowledgements

This research was supported by Korea Institute of Science and Technology Information (KISTI).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jae-Wook Seol
    • 1
  • Won-Jun Choi
    • 1
  • Hee-Seok Jeong
    • 1
  • Hye-Kyong Hwang
    • 1
  • Hwa-Mook Yoon
    • 1
    Email author
  1. 1.Korea Institute of Science and Technology InformationSeoulKorea

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