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- W2030636316 abstract "Summarization techniques have become increasingly important over the last few years, specially in biomedical research, where information overload is major problem. Researchers of this area need a shorter version of the texts which contains all the important information while discarding irrelevant one. There are several applications which deal with this problem, however, these applications are sometimes less informative than the user needs. This work deals with this problem trying to improve a summarization graph-based process using genetic clustering techniques. Our automatic summaries are compared to those produced by several commercial and research summarizers, and demonstrate the appropriateness of using genetic techniques in automatic summarization." @default.
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- W2030636316 date "2013-06-12" @default.
- W2030636316 modified "2023-10-16" @default.
- W2030636316 title "A genetic graph-based clustering approach to biomedical summarization" @default.
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- W2030636316 doi "https://doi.org/10.1145/2479787.2479807" @default.
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