FEMsum: A flexible eclectic multitask summarizer architecture evaluated in multidocument tasks
This article describes two types of summarization approaches integrated in a flexible architecture for multitask summarization. The first type is based on the use of lexical features, while the second one is grounded on syntactic and semantic information. All the approaches have been evaluated in ex...
| Autores: | , , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2007 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/87422 |
| Acceso en línea: | https://hdl.handle.net/2117/87422 |
| Access Level: | acceso abierto |
| Palabra clave: | Text Summarization Spontaneous Speech Summarization Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural |
| Sumario: | This article describes two types of summarization approaches integrated in a flexible architecture for multitask summarization. The first type is based on the use of lexical features, while the second one is grounded on syntactic and semantic information. All the approaches have been evaluated in experiments where, given a set of documents, they are expected to produce summaries answering a user need (expressed by a query) in a reduced set of relevant textual fragments. Their performance is analyzed in two different tasks: written news and scientific oral presentations. |
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