From Unstructured Data to Narrative Abstractive Summaries
| Autor: | Saquete Boró, Estela |
|---|---|
| Přispěvatelé: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos, Procesamiento del Lenguaje y Sistemas de Información (GPLSI) |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | RUA. Repositorio Institucional de la Universidad de Alicante Universidad de Alicante (UA) |
| Popis: | To provide with easy and optimal access to digital information, narrative summaries must have a coherent and natural structure. Depending on how a summary is produced, a distinction can be made between extractive and abstractive summaries. Using an abstractive summarization approach, the relevant information (e.g., who? what?, when?, where?,...) could be fused together, leading to the generation of one or more new sentences. However, in order to do this it is necessary to obtain and process the temporal information in a text. A very effective way is the generation of timelines starting from multiple documents so that the generation of summaries is supported by the generated timeline, without losing the relevant temporal information of the texts. In this proposal, a enriched timeline is generated automatically, and the process of generating abstractive summaries is presented using this timeline as a basis [Barros et al., 2019]. Finally, potential applications of the automatic timeline generation would be presented, as for example its application to Fake News detection. This research work has been partially funded by the projects PROMETEU/2018/089 and RTI2018-094653-B-C22. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|