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Investigating the quality of reverse geocoding services using text similarity techniques and logistic regression analysis / Batuhan Kilic in Cartography and Geographic Information Science, Vol 47 n° 4 (July 2020)
[article]
Titre : Investigating the quality of reverse geocoding services using text similarity techniques and logistic regression analysis Type de document : Article/Communication Auteurs : Batuhan Kilic, Auteur ; Fatih Gülgen, Auteur Année de publication : 2020 Article en page(s) : pp 336 - 349 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] exploration de texte
[Termes IGN] géocodage inverse
[Termes IGN] géocodage par adresse postale
[Termes IGN] logique binaire
[Termes IGN] qualité des données
[Termes IGN] régression
[Termes IGN] similitude sémantiqueRésumé : (auteur) Location, usually defined by postal address information or geographic coordinate values, is one of the leading themes in geography. Famous global mapping services such as ArcGIS Online, Bing Maps, Google Maps, or Yandex Maps can provide users with address information of any geographic coordinates using reverse geocoding. The accuracy of retrieved addresses is quite essential for a service user. Several researchers have evaluated the accuracy of the process based on the positional errors between the retrieved and actual addresses. This article proposes a different assessment based on text similarity algorithms. In this study, the authors examine the outcomes of 15 different text similarity algorithms by comparing them with the reference data. They benefit from the binary logistic regression to evaluate the results. At the end of the case study, they conclude that the soft-term frequency/inverse document frequency algorithm is the most appropriate to measure the quality of postal addresses of all tested services. The Jaccard algorithm also produces successful results only for Google and Bing Maps services. Moreover, the study allows the reader to assess the results of reverse geocoding derived from the global map platforms that serve in the test region. Numéro de notice : A2020-339 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1746198 Date de publication en ligne : 20/04/2020 En ligne : https://doi.org/10.1080/15230406.2020.1746198 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95214
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