Gemedoc: A text similarity annotation platform

Fize Jacques, Roche Mathieu, Teisseire Maguelonne. 2018. Gemedoc: A text similarity annotation platform. In : Natural language processing and information systems: 23rd International Conference on Applications of Natural Language to Information Systems, NLDB 2018, Paris, France, June 13-15, 2018, Proceedings. Silberztein Max (ed.), Atigui Faten (ed.), Kornyshova Elena (ed.), Métais Elisabeth (ed.), Meziane Farid (ed.). CNAM. Cham : Springer, 333-336. (Lecture Notes in Computer Science, 10859) ISBN 978-3-319-91946-1 International Conference on Natural Language to Information Systems. 23, Paris, France, 13 Juin 2018/15 Juin 2018.

Résumé : We present Gemedoc, a platform for text similarity annotation based on the spatial and the thematic dimension. To this end, a two-step annotation protocol was designed to assess the similarity between two documents: (1) identification of salient features according to the two analysis dimensions; (2) similarity assessment according to a 4-degree scale. Ultimately, the labeled data retrieved from different corpora could be used as benchmark for text-mining applications.

Mots-clés libres : Spatial data mining, Heterogeneous data, Text mining

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/588240/)

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