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. © 2009 Springer Berlin Heidelberg.
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CITATION STYLE
Forst, J. F., Tombros, A., & Roelleke, T. (2009). Less is more: Maximal marginal relevance as a summarisation feature. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5766 LNCS, pp. 350–353). https://doi.org/10.1007/978-3-642-04417-5_37
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