Abstract
Summarisation approaches aim to provide the most salient concepts of a text in a condensed representation. Repetition of extracted material in the generated summary should be avoided. Carbonell and Goldstein proposed Maximal Marginal Relevance as a measure to increase the diversity of documents retrieved by an IR system, and developed a summariser based on MMR. In this paper, we look at the viability of MMR as a feature in the traditional feature-based summarisation approach proposed by Edmundson.
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References
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© 2009 Springer-Verlag Berlin Heidelberg
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Forst, J.F., Tombros, A., Roelleke, T. (2009). Less Is More: Maximal Marginal Relevance as a Summarisation Feature. In: Azzopardi, L., et al. Advances in Information Retrieval Theory. ICTIR 2009. Lecture Notes in Computer Science, vol 5766. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04417-5_37
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DOI: https://doi.org/10.1007/978-3-642-04417-5_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04416-8
Online ISBN: 978-3-642-04417-5
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