International Journal of Knowledge Content Development & Technology

Research Institute for Knowledge Content Development & Technology (건국대학교 지식콘텐츠연구소)
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A Study on Developing and Refining a Large Citation Service System

  • Kim, Kwang-Young (Department of Overseas Information, Korea Institute of Science and Technology Information) ;
  • Kim, Hwan-Min (Department of Overseas Information, Korea Institute of Science and Technology Information)
  • Published : 2013.06.30
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Abstract

Today, citation index information is used as an outcome scale of spreading technology and encouraging research. Article citation information is an important factor to determine the authority of the relevant author. Google Scholar uses the article citation information to organize academic article search results with a rank algorithm. For an accurate analysis of such important citation index information, large amounts of bibliographic data are required. Therefore, this study aims to build a fast and efficient system for large amounts of bibliographic data, and to design and develop a system for quickly analyzing cited information for that data. This study also aims to use and analyze citation data to be a basic element for providing various advanced services to the academic article search system.

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References

  1. An, Yuan, Jeannette Janssen, & Evangelos E. Milios. (2004). Characterizing and Mining the Citation Graph of the Computer Science Literature. Knowledge and Information Systems, 6(6), 664-678. https://doi.org/10.1007/s10115-003-0128-3
  2. Beel, Joran, & Bela Gipp. (2009). Google Scholar's Ranking Algorithm: The Impact of Citation Counts. International Conference on Information Technology, 439-446.
  3. Jeong, B. K. (2011). The future society and big data, 13-15, NIPA.
  4. Jung, Eun-Kyoung, Byung-Kyu Kim, & Seon-Heui Choi. (20101). Application and Effect Analysis of DOI based Service for National Academic Information, Proceedings of the Korean Society for Information Management Conference Proceedings of the Korean Society for Information Management Conference, 29-32.
  5. Jung, Eun-Kyoung, Byung-Kyu Kim, & Seon-Heui Choi. (2011). Application System Plan for Scholarly Information Producer using the result of Cited-by linking based on CrossRef DOI. Proceedings of the Korea Information Processing Society Conference, 18(1), 1573-1575.
  6. Kim, Ji-Hoon. (2003). A Study on Automatic Extraction of Citation Information for Reference Linking. Journal of the Korean Society for Library and Information Science, 37(1), 238-268. https://doi.org/10.4275/KSLIS.2003.37.1.247
  7. Ko, Seong-Soon, & Sang-Ki Choi. (2005). Analysis on Foreign Journals Seeking Behaviors through Citation analysis. Korea Library and Information Science Society Magazine, l36(1), 441-457.
  8. Lee, Jung-Yeoun, So-Young Yu, & Jae-Yun Lee. (2010). Strategies for Improving Scholarly Information Service with Citation Information. Journal of information Management, 41(1), 43-67. https://doi.org/10.1633/JIM.2010.41.1.043
  9. The CrossRef. [cited 2013.03.09].
  10. The DBLP. [cited 2013.05.06].
  11. The KSCI. [cited 2013.05.06].
  12. The Mongo DB. [cited 2013.05.07].
  13. The NOSQL. [cited 2013.05.07].
  14. The Plos One. [cited 2013.03.09].
  15. The Thomson returers. [cited 2013.05.06].
  16. The KCI. [cited 2013.05.14].

Cited by

  1. Citation Analysis for Biomedical and Health Sciences Journals Published in Korea vol.23, pp.3, 2017, https://doi.org/10.4258/hir.2017.23.3.218