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| Automatic summarization algorithm based on wordsentence coranking |
| 1. School of Information and Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu 210046, China; 2. Jiangsu Provincial Key Laboratory of EBusiness, Nanjing University of Finance and Economics, Nanjing, Jiangsu 210003, China |
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Abstract To improve the quality of automatic summarization, the graphbased wordsentence coranking method was investigated. Automatic summarization aims to extract a number of sentences from original document to form the socalled extractive summary. Sentence ranking is one of the typical techniques for automatic summarization. Existing studies commonly construct a network of words or sentences and employ PageRank to obtain the ranking scores. Based on the interaction between word and sentence， a novel wordsentence coranking method was proposed for automatic summarization. The importance of words was incorporated into the ranking process on the network of sentences, while the weight of every word was determined by all sentences containing the word. Based on redundancy， a sentence selection method was presented for further improving the quality of autogenerated summary. The experimental results on ten Chinese documents demonstrate that compared with the ranking method only on sentence network， the proposed method can significantly improve the precision and recall rate of automatic summaries.
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2016, Vol. 37 
