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GRU-based capsule network with an improved loss for personnel performance prediction

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Abstract

Personnel performance is a key factor to maintain core competitive advantages. Thus, predicting personnel future performance is a significant research domain in human resource management (HRM). In this paper, to improve the performance, we propose a novel method for personnel performance prediction which helps decision-makers select high-potential talents. Specifically, for modeling the personnel performance, we first devise a GRU model to learn sequential information from personnel performance data without any expertise. Then, to better cluster the features, we exploit capsule network. Finally, to precisely make predictions, we further design one strategy, i.e., an improved loss function, and embed it into the capsule network. In addition, by introducing this strategy, our proposed model can well deal with the imbalanced data problem. Extensive experiments on real-world data clearly demonstrate the effectiveness of the proposed approach.

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Acknowledgements

This work was sponsored by the Key Research and Development Program in Shaanxi Province of China (No.2019ZDLGY03-10), the National Natural Science Foundation Projects of China (No.61877050), the Major Issues of Basic Education in Shaanxi Province of China (No.ZDKT1916) and the Natural Science Foundation of Shaanxi Province (No.2019JZ-47).

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Authors and Affiliations

  1. School of Information Science and Technology, Northwest University, Xi’an, 710127, China

    Xia Xue, Yi Gao, Meng Liu, Xia Sun & Jun Feng

  2. Maths and Information Technology School, Yuncheng University, Yuncheng, 044000, China

    Xia Xue

  3. Xi’an University of Posts and Telecommunications, College of Economic and Management, Xi’an, 710016, China

    Wenyu Zhang

  4. China Aerospace Academy of Systems Science and Engineering, Beijing, 100048, China

    Wenyu Zhang

  5. State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, Northwest University, Xi’an, 710127, Shaanxi, China

    Jun Feng

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  1. Xia Xue
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  2. Yi Gao
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  3. Meng Liu
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  4. Xia Sun
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  5. Wenyu Zhang
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  6. Jun Feng
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Correspondence to Xia Sun or Jun Feng.

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Xue, X., Gao, Y., Liu, M. et al. GRU-based capsule network with an improved loss for personnel performance prediction. Appl Intell 51, 4730–4743 (2021). https://doi.org/10.1007/s10489-020-02039-x

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