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Could spatial features help the matching of textual data?

Fize Jacques, Roche Mathieu, Teisseire Maguelonne. 2020. Could spatial features help the matching of textual data?. Intelligent Data Analysis, 24 (5) : pp. 1043-1064.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Url - jeu de données : https://doi.org/10.18167/DVN1/8LIG1D / Url - jeu de données : https://doi.org/10.18167/DVN1/KH7YTO / Url - jeu de données : https://doi.org/10.18167/DVN1/JLXBLA

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Psychologie-éthologie-ergonomie

Abstract : Textual data is available to an increasing extent through different media (social networks, companies data, data catalogues, etc.). New information extraction methods are needed since these new resources are highly heterogeneous. In this article, we propose a text matching process based on spatial features and assessed through heterogeneous textual data. Besides being compatible with heterogeneous data, it comprises two contributions: first, spatial information is extracted for comparison purposes and subsequently stored in a dedicated spatial textual representation (STR); and then two transformations are applied on STR to improve the spatial similarity estimation. This article outlines the proposed approach with new contributions: (i) a new geocoding methods using general co-occurrences between entities, and (ii) a thorough evaluation followed by (iii) an in-depth discussion. The results obtained on two corpora demonstrate that good spatial matches (≈ 80% precision on major criteria) can be obtained between the most similar STRs with further enhancement achieved via STR transformation.

Mots-clés Agrovoc : Analyse de données, Données, Traitement de l'information, données spatiales

Mots-clés complémentaires : fouille de texte, Analyse spatiale, analyse de texte, données textuelles, Représentation graphique

Mots-clés libres : Text Mining, Spatial analysis, Heterogeneous data, Text matching, Graph matching, Spatial similarity

Classification Agris : C30 - Documentation and information
U10 - Computer science, mathematics and statistics
B10 - Geography

Champ stratégique Cirad : CTS 5 (2019-) - Territoires

Auteurs et affiliations

Source : Cirad-Agritrop (https://agritrop.cirad.fr/596819/)

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