[4Rin1-35] News Headline Generation Based on Reinforcement Learning Considering Human Evaluation
Keywords:Headline Generation, Reinforcement Learning, Crowdsourcing
This paper proposes a method for generating headlines based on reinforcement learning, considering the human evaluation of an entire headline. First, we evaluate which headline is better by crowdsourcing, headlines by editors or headlines by a baseline system, and we train a headline-pair evaluator using these data. Then, a headline generation model is trained based on reinforcement learning where the prediction of the evaluator is used as a reward. Experimental results demonstrated that the proposed method could generate better headlines in comparison with several baseline systems.
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