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Weakly Supervised Abstractive Summarization with Enhancing Factual Consistency for Chinese Complaint Reports
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作者 Ren Tao Chen Shuang 《Computers, Materials & Continua》 SCIE EI 2023年第6期6201-6217,共17页
A large variety of complaint reports reflect subjective information expressed by citizens.A key challenge of text summarization for complaint reports is to ensure the factual consistency of generated summary.Therefore... A large variety of complaint reports reflect subjective information expressed by citizens.A key challenge of text summarization for complaint reports is to ensure the factual consistency of generated summary.Therefore,in this paper,a simple and weakly supervised framework considering factual consistency is proposed to generate a summary of city-based complaint reports without pre-labeled sentences/words.Furthermore,it considers the importance of entity in complaint reports to ensure factual consistency of summary.Experimental results on the customer review datasets(Yelp and Amazon)and complaint report dataset(complaint reports of Shenyang in China)show that the proposed framework outperforms state-of-the-art approaches in ROUGE scores and human evaluation.It unveils the effectiveness of our approach to helping in dealing with complaint reports. 展开更多
关键词 Automatic summarization abstractive summarization weakly supervised training entity recognition
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