A hybrid sentence ordering strategy in multi-document summarzation

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Abstract

In extractive summarization, a proper arrangement of extracted sentences must be found if we want to generate a logical, coherent and readable summary. This issue is special in multi-document summarization. In this paper, several existing methods each of which generate a reference relation are combined through linear combination of the resulting relations. We use 4 types of relationships between sentences (chronological relation, positional relation, topical relation and dependent relation) to build a graph model where the vertices are sentences and edges are weighed relationships of the 4 types. And then apply a variation of page rank to get the ordering of sentences for multidocument summaries. We tested our hybrid model with two automatic methods: distance to manual ordering and ROUGE score. Evaluation results show a significant improvement of the ordering over strategies losing some relations. The results also indicate that this hybrid model is robust for articles with different genre which were used on DUC2004 and DUC2005. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Yanxiang, H., Dexi, L., Hua, Y., Donghong, J., Chong, T., & Wenqing, Q. (2006). A hybrid sentence ordering strategy in multi-document summarzation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4255 LNCS, pp. 339–349). Springer Verlag. https://doi.org/10.1007/11912873_35

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