In this article, we present the current state of our work on a linguistically-motivated model for automatic summarization of medical articles in Spanish. The model takes into account the results of an empirical study which reveals that, on the one hand, domain-specific summarization criteria can often be derived from the summaries of domain specialists, and, on the other hand, adequate summarization strategies must be multidimensional, i.e., cover various types of linguistic clues. We take into account the textual, lexical, discursive, syntactic and communicative dimensions. This is novel in the field of summarization. The experiments carried out so far indicate that our model is suitable to provide high quality summarizations.
2021. Análisis multimodal de los principales géneros académicos en la formación del profesional y técnico en Enfermería. Círculo de Lingüística Aplicada a la Comunicación 85 ► pp. 211 ff.
Zhang, Hongxin & Haitao Liu
2016. Visualizing structural “inverted pyramids” in English news discourse across levels. Text & Talk 36:1 ► pp. 89 ff.
Laureano-Cruces, Ana Lilia & Javier Ramírez-Rodríguez
2012. A Graph-Based Summarization System at QAINEX Track 2011. In Focused Retrieval of Content and Structure [Lecture Notes in Computer Science, 7424], ► pp. 227 ff.
Vivaldi, Jorge, Iria da Cunha & Javier Ramírez
2011. The REG Summarization System with Question Reformulation at QAINEX Track 2010. In Comparative Evaluation of Focused Retrieval [Lecture Notes in Computer Science, 6932], ► pp. 295 ff.
da Cunha, Iria & Mikel Iruskieta
2010. Comparing rhetorical structures in different languages: The influence of translation strategies. Discourse Studies 12:5 ► pp. 563 ff.
[no author supplied]
2014. Bibliography. In Automatic Text Summarization, ► pp. 309 ff.
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