Machine Learning of Generic and User-Focused Summarization

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A key problem in text summarization is finding a salience function which determines what information in the source should be included in the summary. This paper describes the use of machine learning on a training corpus of documents and their abstracts to discover salience functions which describe what combination of features is optimal for a given summarization task. The method addresses both "generic" and user-focused summaries.
In Proceedings of the Fifteenth National Conference on AI (AAAI-98), p. 821-826

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Computation and Language, Machine Learning, I.2.6; I.2.7

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http://salesiana.dossiersoluciones.com/handle/123456789/33079

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cs/9811006
 http://arxiv.org/abs/cs/9811006

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arXiv