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A Domain Knowledge Based Method on Automatic Generation of Information Requirement Against Big Data

In: Liss 2014

Author

Listed:
  • Xin Jin

    (Nanjing Research Institute of Electronics Engineering)

  • Shiqiang Zong

    (Nanjing Research Institute of Electronics Engineering)

  • Youjiang Li

    (Nanjing Research Institute of Electronics Engineering)

  • Jingjing Yan

    (Nanjing Research Institute of Electronics Engineering)

  • Shanshan Wu

    (Nanjing Research Institute of Electronics Engineering)

Abstract

Increasing number of enterprises are mining Big Data for decision support, but they found Big Data not quite as usable as their own well organized databases. Useful information is hidden within Big Data, and could only be found by search, according to keywords, queries or other kinds of requirement express patterns. It is found that during decision making process, user information requirement highly depends on the decision task, that on processing tasks of a same type, requirements have similar content and scope. Based on this principle, a method is proposed to automatically generate information requirement against Big Data, by making use of a new kind of domain knowledge—the latent mapping relations among decision task types and information requirement models. It is proved by tests that, the method can improve efficiency of decision support information collection from Big Data.

Suggested Citation

  • Xin Jin & Shiqiang Zong & Youjiang Li & Jingjing Yan & Shanshan Wu, 2015. "A Domain Knowledge Based Method on Automatic Generation of Information Requirement Against Big Data," Springer Books, in: Zhenji Zhang & Zuojun Max Shen & Juliang Zhang & Runtong Zhang (ed.), Liss 2014, edition 127, pages 731-739, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-43871-8_105
    DOI: 10.1007/978-3-662-43871-8_105
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