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A Deep Learning Model for Mining Behavioral Preference of Home Care Demanders to Suppliers

In: City, Society, and Digital Transformation

Author

Listed:
  • Hongying Fei

    (Shanghai University)

  • Mingzhu Xu

    (Shanghai University)

Abstract

This study aims at developing a deep learning prediction model for the preference of home care service demanders to suppliers available in a health care management platform. Firstly, a Node2vec-based algorithm enhanced by minimizing patients’ preference difference, is developed for capturing behavioural pattern of demanders; then an advanced deep learning GRU model, combing attention mechanism for service categories, is constructed to predict the visiting preference to various service suppliers by taking into account not only the constraints of technical requirement but also personal behavioural preference. Experimental results show that the proposed deep learning model, compared to the traditional deep learning GRU model, can significantly improve the quality of behavioural preference prediction, which can help improve the recommendation success rate of service suppliers to demanders.

Suggested Citation

  • Hongying Fei & Mingzhu Xu, 2022. "A Deep Learning Model for Mining Behavioral Preference of Home Care Demanders to Suppliers," Lecture Notes in Operations Research, in: Robin Qiu & Wai Kin Victor Chan & Weiwei Chen & Youakim Badr & Canrong Zhang (ed.), City, Society, and Digital Transformation, chapter 0, pages 203-215, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-15644-1_16
    DOI: 10.1007/978-3-031-15644-1_16
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