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Knowledge acquisition model of mobile payment based on automatic summary technology

Author

Listed:
  • Huosong Xia

    (Wuhan Textile University
    Key Research Institute of Humanities and Social Sciences in Universities of Hubei Province)

  • Jing Liu

    (Wuhan Textile University)

  • Justin Zuopeng Zhang

    (University of North Florida)

  • Lakshmi Goel

    (University of North Florida)

  • Yuan Wang

    (Wuhan Textile University)

Abstract

The risks in mobile payment under Fintech have become an urgent problem to be addressed. This paper develops a research framework of knowledge acquisition and explores how automatic summarization technology helps extract knowledge of mobile payment to help managers and users reduce the financial risks. Specifically, we construct the mobile payment domain thesaurus and propose an automatic summary extraction model that integrates Bi-directional Long Short-Term Memory (BiLSTM), Attention Mechanism, and Reinforcement Learning (RL). The model is then used to extract the summary of mobile payment policy documents for knowledge acquisition. Our proposed model performs better than other basic models in Rouge-2, Rouge-4, and Rouge-SU4 indexes. Our study enriches relevant research in the existing literature, facilitates knowledge acquisition in mobile payment, and helps mobile users and managers reduce financial risks in their operations.

Suggested Citation

  • Huosong Xia & Jing Liu & Justin Zuopeng Zhang & Lakshmi Goel & Yuan Wang, 2024. "Knowledge acquisition model of mobile payment based on automatic summary technology," Electronic Commerce Research, Springer, vol. 24(1), pages 131-154, March.
    • Handle: RePEc:spr:elcore:v:24:y:2024:i:1:d:10.1007_s10660-022-09553-9
    DOI: 10.1007/s10660-022-09553-9
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