@inproceedings{lee-lee-2017-automatic,
title = "Automatic Text Summarization Using Reinforcement Learning with Embedding Features",
author = "Lee, Gyoung Ho and
Lee, Kong Joo",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-2033",
pages = "193--197",
abstract = "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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%0 Conference Proceedings
%T Automatic Text Summarization Using Reinforcement Learning with Embedding Features
%A Lee, Gyoung Ho
%A Lee, Kong Joo
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F lee-lee-2017-automatic
%X 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.
%U https://aclanthology.org/I17-2033
%P 193-197
Markdown (Informal)
[Automatic Text Summarization Using Reinforcement Learning with Embedding Features](https://aclanthology.org/I17-2033) (Lee & Lee, IJCNLP 2017)
ACL