Mapping heterogeneous textual data: a multidimensional approach based on spatiality and theme

Fize Jacques, Roche Mathieu, Teisseire Maguelonne. 2019. Mapping heterogeneous textual data: a multidimensional approach based on spatiality and theme. In : Internet science : 6th International Conference, INSCI 2019, Perpignan, France, December 2–5, 2019, Proceedings. El Yacoubi Samira (ed.), Bagnoli Franco (ed.), Pacini Giovanna (ed.). IMAGES Epaces-DEV, University of Perpignan. Cham : Springer, 310-317. (Lecture Notes in Computer Science, 11938) ISBN 978-3-030-34769-7 International Conference on Internet Science (INSCI 2019). 6, Perpignan, France, 2 Décembre 2019/5 Décembre 2019.

Résumé : In this paper, we propose a multidimensional mapping approach for heterogeneous textual data that exploits firstly the spatial dimension and secondly the thematic dimension. Based on the Spatial Textual Representation (STR) as well as the Geodict geographic database, the contribution presented in this paper integrates the thematic dimension of documents. To support our proposal on mapping textual documents, we evaluate the different aspects of the process using two real corpora, including one corpus that is highly heterogeneous.

Mots-clés libres : Text mining, Spatial data mining, Natural language processing, Data mining, Heterogeneous data

Auteurs et affiliations

• Fize Jacques, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-1783-934X
• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568
• Teisseire Maguelonne, IRSTEA (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/594529/)

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