Centre de documentation
scientifique

Automatic identification of addresses: A systematic literature review / Paula Cruz in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 1 (January 2022) . - n° 11 Titre : Automatic identification of addresses: A systematic literature review Type de document : Article/Communication Auteurs : Paula Cruz, Auteur ; Leonardo Vanneschi, Auteur ; Marco Painho, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] appariement d'adresses [Termes IGN] apprentissage automatique [Termes IGN] apprentissage profond [Termes IGN] base de données d'adresses [Termes IGN] géocodage par adresse postale [Termes IGN] Geoparsing [Termes IGN] service fondé sur la position Résumé : (auteur) Address matching continues to play a central role at various levels, through geocoding and data integration from different sources, with a view to promote activities such as urban planning, location-based services, and the construction of databases like those used in census operations. However, the task of address matching continues to face several challenges, such as non-standard or incomplete address records or addresses written in more complex languages. In order to better understand how current limitations can be overcome, this paper conducted a systematic literature review focused on automated approaches to address matching and their evolution across time. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, resulting in a final set of 41 papers published between 2002 and 2021, the great majority of which are after 2017, with Chinese authors leading the way. The main findings revealed a consistent move from more traditional approaches to deep learning methods based on semantics, encoder-decoder architectures, and attention mechanisms, as well as the very recent adoption of hybrid approaches making an increased use of spatial constraints and entities. The adoption of evolutionary-based approaches and privacy preserving methods stand as some of the research gaps to address in future studies. Numéro de notice : A2022-088 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi11010011 Date de publication en ligne : 29/12/2021 En ligne : https://doi.org/10.3390/ijgi11010011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99497 [article]