Abstract
In the group argumentation environment, a large amount of text information will be produced. How to find the specific speeches of experts from many similar speeches and extract their common summary is of great significance to improve the efficiency of experts’ argumentation and promote consensus. In this paper, the heuristic method is first used to cluster the speech texts and find the similar speech sets. Then, we use TextRank algorithm to extract multiple document summary, and feedback the summary to the experts. The experimental results show that the efficiency of the experts’ argumentation is improved and the decision-making is promoted.
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This research is supported by National Natural Science Foundation of China under grant number 61075059, 61300127.
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Xiong, C., Li, Y., Lv, K. (2018). Multi-documents Summarization Based on the TextRank and Its Application in Argumentation System. In: Barolli, L., Zhang, M., Wang, X. (eds) Advances in Internetworking, Data & Web Technologies. EIDWT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-59463-7_45
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DOI: https://doi.org/10.1007/978-3-319-59463-7_45
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