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
Final Paper
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.
Important Date
  • Conference Date

    Jun 12

    2019

    to

    Jun 14

    2019

  • Jun 12 2019

    Draft paper submission deadline

  • Jun 14 2019

    Registration deadline

Organized By
Xi'an University of Technology
Contact Information