Automatic generation of entity-oriented summaries for reputation management
| Autor: | Felisa Verdejo, Laura Plaza, Julio Gonzalo, Enrique Amigó, Javier Rodríguez-Vidal, Jorge Carrillo-de-Albornoz |
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| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Computer science media_common.quotation_subject Analogy Computational intelligence Context (language use) 02 engineering and technology Data science Automatic summarization Test (assessment) Task (project management) 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Reputation management Reputation media_common |
| Zdroj: | Journal of Ambient Intelligence and Humanized Computing. 11:1577-1591 |
| ISSN: | 1868-5145 1868-5137 |
| DOI: | 10.1007/s12652-019-01255-9 |
| Popis: | Producing online reputation summaries for an entity (company, brand, etc.) is a focused summarization task with a distinctive feature: issues that may affect the reputation of the entity take priority in the summary. In this paper we (i) present a new test collection of manually created (abstractive and extractive) reputation reports which summarize tweet streams for 31 companies in the banking and automobile domains; (ii) propose a novel methodology to evaluate summaries in the context of online reputation monitoring, which profits from an analogy between reputation reports and the problem of diversity in search; and (iii) provide empirical evidence that producing reputation reports is different from a standard summarization problem, and incorporating priority signals is essential to address the task effectively. |
| Databáze: | OpenAIRE |
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