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A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements / Yingjie Hu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 3-4 (March - April 2019) . - pp 714 - 738 Titre : A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements Type de document : Article/Communication Auteurs : Yingjie Hu, Auteur ; Huina Mao, Auteur ; Grant McKenzie, Auteur Année de publication : 2019 Article en page(s) : pp 714 - 738 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie [Termes IGN] analyse de groupement [Termes IGN] information sémantique [Termes IGN] publicité [Termes IGN] recherche d'information géographique [Termes IGN] reconnaissance de noms [Termes IGN] répertoire toponymique [Termes IGN] toponymie locale [Termes IGN] traitement du langage naturel Résumé : (Auteur) Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework. Numéro de notice : A2019-213 Affiliation des auteurs : non IGN Thématique : TOPONYMIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1458986 Date de publication en ligne : 13/04/2018 En ligne : https://doi.org/10.1080/13658816.2018.1458986 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92685 [article]

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