JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2021, Vol. 56 ›› Issue (1): 83-90.doi: 10.6040/j.issn.1671-9352.4.2020.131

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Research on matching resumes and positions based on Arc-LSTM

XU Fei-fei1, XU Yun-jie2   

  1. 1. College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China;
    2. Process and IT Platform Software Development BU, COMAC Shanghai Aviation Industrial(Group), Shanghai 200232, China
  • Published:2021-01-05

Abstract: An automatic scheme is proposed, which combines the deep neural network Arc-LSTM with Word2Vec model. In this paper, the CBOW model is used to extract resume text features. A new deep neural network, Arc-LSTM is put forward, which is optimized by ArcReLU. The experimental results show that Arc-LSTM can effectively improve the classification accuracy and convergence speed, and achieve the exact match between Chinese resumes and positions.

Key words: deep learning, activation function, job matching, ArcReLU, Arc-LSTM

CLC Number: 

  • TP18
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