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• W2952831072 abstract "We propose a summarization approach for scientific articles which takes advantage of citation-context and the document discourse model. While citations have been previously used in generating scientific summaries, they lack the related context from the referenced article and therefore do not accurately reflect the article's content. Our method overcomes the problem of inconsistency between the citation summary and the article's content by providing context for each citation. We also leverage the inherent scientific article's discourse for producing better summaries. We show that our proposed method effectively improves over existing summarization approaches (greater than 30% improvement over the best performing baseline) in terms of textsc{Rouge} scores on TAC2014 scientific summarization dataset. While the dataset we use for evaluation is in the biomedical domain, most of our approaches are general and therefore adaptable to other domains." @default.
• W2952831072 created "2019-06-27" @default.
• W2952831072 creator A5036610566 @default.
• W2952831072 creator A5064858748 @default.
• W2952831072 date "2017-04-21" @default.
• W2952831072 modified "2023-09-27" @default.
• W2952831072 title "Scientific Article Summarization Using Citation-Context and Article's Discourse Structure" @default.
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• W2952831072 hasPublicationYear "2017" @default.
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