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A two-step deep learning approach to data classification and modeling and a demonstration on subject type relationship analysis in the Web of Science

Author

Listed:
  • Frederick Kin Hing Phoa

    (Academia Sinica)

  • Hsin-Yi Lai

    (National Chiao Tung University)

  • Livia Lin-Hsuan Chang

    (SOKENDAI (The Graduate University for Advanced Studies))

  • Keisuke Honda

    (Institute of Statistical Mathematics)

Abstract

It is common sense that some subjects have strong relationships while others are perhaps almost mutually independent, but a quantitative and systematic approach to describe such sense is a deficiency. A technique called pointwise mutual information (PMI) from information science helps to fulfill the request, but the calculation through a large-scale database is computationally infeasible if one requires an instantaneous value. This work provides a two-step remedy via deep learning for estimating and predicting relationships among two subject types that are found in the large-scale citation database called the Web of Science. The resulting model successfully replicates existing PMI values among subject types, and it can be used for predicting PMI values of two subject types if one or both subject types does not exist in the database.

Suggested Citation

  • Frederick Kin Hing Phoa & Hsin-Yi Lai & Livia Lin-Hsuan Chang & Keisuke Honda, 2020. "A two-step deep learning approach to data classification and modeling and a demonstration on subject type relationship analysis in the Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 851-863, November.
    • Handle: RePEc:spr:scient:v:125:y:2020:i:2:d:10.1007_s11192-020-03599-y
    DOI: 10.1007/s11192-020-03599-y
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    References listed on IDEAS

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    1. Wang, Tai-Chi & Phoa, Frederick Kin Hing, 2016. "A scanning method for detecting clustering pattern of both attribute and structure in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 295-309.
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    Cited by:

    1. Chester Wai-Jen Liu & Sheng-Feng Shen & Wei-Chung Liu, 2021. "On the evolution of social ties as an instrumental tool for resource competition in resource patch networks," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-18, December.

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