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A comparison of geometric approaches to assessing spatial similarity for GIR / P. Frontiera in International journal of geographical information science IJGIS, vol 22 n° 3 (march 2008)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 22 n° 3 (march 2008) . - pp 337 - 360 Titre : A comparison of geometric approaches to assessing spatial similarity for GIR Type de document : Article/Communication Auteurs : P. Frontiera, Auteur ; R. Larson, Auteur ; J. Radke, Auteur Année de publication : 2008 Article en page(s) : pp 337 - 360 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] approximation [Termes IGN] indexation spatiale [Termes IGN] pertinence [Termes IGN] recherche d'information géographique [Termes IGN] requête spatiale [Termes IGN] similitude Résumé : (Auteur) This research compares the geographic information retrieval (GIR) performance of a set of logistic regression models with those of five non-probabilistic methods that compute a spatial similarity score for a query-document pair. All methods are applied to a test collection of queries and documents indexed spatially by two convex conservative geometric approximations: the minimum bounding box (MBB) and the convex hull. In the comparison, the tested logistic regression models outperform, in terms of standard information retrieval recall and precision measures, all of the non-probabilistic methods. The retrieval performance achieved by the logistic regression models on MBB approximations is similar to that achieved by the use of the non-probabilistic methods on convex hulls. Although these results are valid only for the test collection used in this study, they suggest that a logistic regression approach to GIR provides an alternative to the use of higher-quality geometric representations that are more difficult to obtain, implement, and process. Additionally, this research demonstrates the ability of a probabilistic approach to effectively incorporate information about geographic context in the spatial ranking process. Copyright Taylor & Francis Numéro de notice : A2008-143 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810701626293 En ligne : https://doi.org/10.1080/13658810701626293 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29138 [article]

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