Artículo
A deep-learning approach to mining conditions
Autor/es | Gallego, Fernando O.
Corchuelo Gil, Rafael |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2020-04 |
Fecha de depósito | 2023-03-07 |
Publicado en |
|
Resumen | A condition is a constraint that determines when a consequent holds. Mining them in text is paramount to understand many sentences properly. In the literature, there are a few pattern-based proposals that fall short regarding ... A condition is a constraint that determines when a consequent holds. Mining them in text is paramount to understand many sentences properly. In the literature, there are a few pattern-based proposals that fall short regarding recall because it is not easy to characterise unusual ways to express conditions with hand-crafted patterns; there is one machine-learning proposal that is bound to the Japanese language, requires specific-purpose dictionaries, taxonomies, and heuristics, works on opinion sentences only, and was evaluated very shallowly. In this article, we present a deep-learning proposal to mine conditions that does not have any of the previous drawbacks; furthermore, we have performed a comprehensive experimental study on a large multi-lingual dataset on many common topics; our conclusion is that our proposals are similar to the state of the art in terms of precision, but improve recall enough to beat them in terms of F1 score. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España |
Identificador del proyecto | TIN2013-40848-R
TIN2016-75394-R |
Cita | Gallego, F.O. y Corchuelo Gil, R. (2020). A deep-learning approach to mining conditions. Knowledge-Based Systems, 193. https://doi.org/10.1016/j.knosys.2019.105422. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
A deep-learning approach to ... | 2.375Mb | [PDF] | Ver/ | |