Abstract
With the accelerating rate of data growth on the Internet, automatic multi-document summarization has become an important task. In this paper, we propose a link analysis incorporated with rhetorical relations between sentences to perform extractive summarization for multiple-documents. We make use of the documents headlines to extract sentences with salient terms from the documents set using statistical model. Then we assign rhetorical relations learned by SVMs to determine the connectivity between the sentences which include the salient terms. Finally, we rank these sentences by measuring their relative importance within the document set based on link analysis method, PageRank. The rhetorical relations are used to evaluate the complementarity and redundancy of the ranked sentences. Our evaluation results show that the combination of PageRank along with rhetorical relations among sentences does help to improve the quality of extractive summarization.
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Zahri, N.A.H.B., Fukumoto, F. (2011). Multi-document Summarization Using Link Analysis Based on Rhetorical Relations between Sentences. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6609. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19437-5_27
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DOI: https://doi.org/10.1007/978-3-642-19437-5_27
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