Discovering types of spatial relations with a text mining approach

Zenasni Sarah, Kergosien Eric, Roche Mathieu, Teisseire Maguelonne. 2015. Discovering types of spatial relations with a text mining approach. In : Foundations of intelligent systems. Esposito Floriana (ed.), Pivert Olivier (ed.), Hacid Mohand-Said (ed.), Rás Zbigniew W. (ed.), Ferilli Stefano (ed.). Cham : Springer International Publishing, 442-451. (Lecture Notes in Computer Science, 9384) ISBN 978-3-319-25252-0 International Symposium on Methodologies for Intelligent Systems. 22, Lyon, France, 21 Octobre 2015/23 Octobre 2015.

https://doi.org/10.1007/978-3-319-25252-0_47

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Résumé : Knowledge discovery from texts, particularly the identification of spatial information is a difficult task due to the complexity of texts written in natural language. Here we propose a method combining two statistical approaches (lexical and contextual analysis) and a text mining approach to automatically identify types of spatial relations. Experiments conducted on an English corpus are presented.

Mots-clés libres : Spatial relations, Text mining

Classification Agris : C30 - Documentation et information
U10 - Informatique, mathématiques et statistiques

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