Automatic Text Summarization Using Reinforcement Learning with Embedding Features

2017-11-01 · IJCNLP 2017 11 · Gyoung Ho Lee, Kong Joo Lee

An automatic text summarization system can automatically generate a short and brief summary that contains a main concept of an original document. In this work, we explore the advantages of simple embedding features in Reinforcement leaning approach to automatic text summarization tasks. In addition, we propose a novel deep learning network for estimating Q-values used in Reinforcement learning. We evaluate our model by using ROUGE scores with DUC 2001, 2002, Wikipedia, ACL-ARC data. Evaluation results show that our model is competitive with the previous models.

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ARCInformation Retrieval reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)Text Summarization

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