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) : 1043-1064.

Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/8LIG1D / Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/KH7YTO / Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/JLXBLA

Quartile : Q4, Sujet : COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Liste HCERES des revues (en SHS) : oui

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

Résumé : 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, fouille de textes, analyse spatiale

Mots-clés complémentaires : 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 et information
U10 - Informatique, mathématiques et statistiques
B10 - Géographie

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

Auteurs et affiliations

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

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

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