349 / 2019-02-18 22:28:36
Extracting Keywords from Short Government Documents Using Reinforcement Learning
reinforcement learning,keyword extraction,government big data,government document understanding
终稿
Huimin Cai / CETC Big Data Research Institute Co., Ltd.
Ranran Chen / CETC Big Data Research Institute Co., Ltd.
Xiang Li / CETC Big Data Research Institute Co., Ltd.
Qilin Mu / CETC Big Data Research Institute Co., Ltd.
In this paper, we proposed a novel approach to extract keywords from massive amount of unlabelled short government documents using reinforcement learning. To guide policy network to keep important words, we introduced the average rate regularization, as the sparsity constraints of the model's loss function. Analysis on the results shows that the proposed model outperforms the traditional unsupervised keyword extraction approaches on massive amount of unlabelled government document headlines.
重要日期
  • 会议日期

    06月12日

    2019

    06月14日

    2019

  • 06月12日 2019

    初稿截稿日期

  • 06月14日 2019

    注册截止日期

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