Abstract
We describe experiments on content selection for producing biographical summaries from multiple documents. The method relies on a set of patterns to identify descriptive phrases, an available co-reference resolution algorithm, and a greedy, corpus-based sentence deletion procedure for document compression. We show that in an automatic evaluation of content using ROUGE, the proposed method obtains very good performance.
Keywords
- Noun Phrase
- Vector Space Model
- Longe Common Subsequence
- Coreference Resolution
- Target Entity
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Saggion, H., Gaizauskas, R. (2005). Experiments on Statistical and Pattern-Based Biographical Summarization. In: Bento, C., Cardoso, A., Dias, G. (eds) Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science(), vol 3808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595014_60
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DOI: https://doi.org/10.1007/11595014_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30737-2
Online ISBN: 978-3-540-31646-6
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