Multi-document summarization using semantic discourse models
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| Format: | Artículo científico |
| Langue: | en |
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Sociedad Española para el Procesamiento del Lenguaje Natural
2016
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| _version_ | 1876470305003667456 |
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| author | Paula C. F. Cardoso |
| author_facet | Paula C. F. Cardoso |
| contents | Multi-document summarization using semantic discourse models Paula C. F. Cardoso Thiago A. S. Pardo Computación Multi Cross document Summarization document Structure Theory Rhetorical Structure Theory Automatic multi-document summarization aims at reducing the size of texts while preserving the important content. In this paper, we propose some methods for automatic summarization based on two semantic discourse models: Rhetorical Structure Theory (RST) and Cross-document Structure Theory (CST). These models are chosen in order to properly address the relevance of information, multi-document phenomena and subtopical distribution in the source texts. The results show that using semantic discourse knowledge for content selection improve the informativeness of automatic summaries. 2016 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515754423006 en http://www.redalyc.org/revista.oa?id=5157 Procesamiento del Lenguaje Natural application/pdf Sociedad Española para el Procesamiento del Lenguaje Natural Procesamiento del Lenguaje Natural (España) Num.56 |
| format | Artículo científico |
| id | redalyc_515754423006 |
| institution | Redalyc |
| language | en |
| publishDate | 2016 |
| publisher | Sociedad Española para el Procesamiento del Lenguaje Natural |
| spellingShingle | Multi-document summarization using semantic discourse models Paula C. F. Cardoso Computación Multi Cross document Summarization document Structure Theory Rhetorical Structure Theory Multi-document summarization using semantic discourse models Paula C. F. Cardoso Thiago A. S. Pardo Computación Multi Cross document Summarization document Structure Theory Rhetorical Structure Theory Automatic multi-document summarization aims at reducing the size of texts while preserving the important content. In this paper, we propose some methods for automatic summarization based on two semantic discourse models: Rhetorical Structure Theory (RST) and Cross-document Structure Theory (CST). These models are chosen in order to properly address the relevance of information, multi-document phenomena and subtopical distribution in the source texts. The results show that using semantic discourse knowledge for content selection improve the informativeness of automatic summaries. 2016 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515754423006 en http://www.redalyc.org/revista.oa?id=5157 Procesamiento del Lenguaje Natural application/pdf Sociedad Española para el Procesamiento del Lenguaje Natural Procesamiento del Lenguaje Natural (España) Num.56 |
| title | Multi-document summarization using semantic discourse models |
| topic | Computación Multi Cross document Summarization document Structure Theory Rhetorical Structure Theory |
| url | https://www.redalyc.org/articulo.oa?id=515754423006 |