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Automatic Identification of Research Articles Containing Data Usage Statements

In: Knowledge Discovery and Data Design Innovation Proceedings of the International Conference on Knowledge Management (ICKM 2017)

Author

Listed:
  • Qiuzi Zhang
  • Wei Lu
  • Yunhan Yang
  • Haihua Chen
  • Jiangping Chen

Abstract

Modern scientific research is characterized with sharing datasets and reusing data for developing new models and theories. This paper describes a study to identify research articles with data use and reuse information. Applying a bootstrapping-based unsupervised training strategy, we were able to develop text patterns automatically out of a large training collection of research articles. These patterns were then used to distinguish articles with data use and reuse from those without data usage. Our experiments using Computer Science literature showed that the identification could achieve more than 85% pattern extensibility. We also demonstrate how the results of the identification could be utilized to gain insights on data sharing and reuse in a scientific field.

Suggested Citation

  • Qiuzi Zhang & Wei Lu & Yunhan Yang & Haihua Chen & Jiangping Chen, 2017. "Automatic Identification of Research Articles Containing Data Usage Statements," World Scientific Book Chapters, in: Daniel Gelaw Alemneh & Jeff Allen & Suliman Hawamdeh (ed.), Knowledge Discovery and Data Design Innovation Proceedings of the International Conference on Knowledge Management (ICKM 2017), chapter 4, pages 67-87, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789813234482_0004
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    More about this item

    Keywords

    Knowledge Discovery; Big Data; Data Science; Data Analytics; Innovation;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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