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How urban places are visited by social groups? Evidence from matrix factorization on mobile phone data / Chaogui Kang in Transactions in GIS, Vol 24 n° 6 (December 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 6 (December 2020) . - pp 1504 - 1525 Titre : How urban places are visited by social groups? Evidence from matrix factorization on mobile phone data Type de document : Article/Communication Auteurs : Chaogui Kang, Auteur ; Li Shi, Auteur ; Fahui Wang, Auteur ; Yu Liu, Auteur Année de publication : 2020 Article en page(s) : pp 1504 - 1525 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Chine [Termes IGN] contenu généré par les utilisateurs [Termes IGN] données spatiotemporelles [Termes IGN] ethnographie [Termes IGN] factorisation de matrice non-négative [Termes IGN] matrice de co-occurrence [Termes IGN] production participative [Termes IGN] réseau social [Termes IGN] site urbain [Termes IGN] téléphonie mobile [Termes IGN] urbanisme Résumé : (Auteur) This research attempts to build a unified framework for distinguishing the spatiotemporal visit patterns of urban places by different social groups using mobile phone data in Harbin, China. Social groups are detected by their social ties in the ego‐to‐ego mobile phone call network and are embedded in physical space according to their home locations. Popular urban places are detected from user‐generated content as the basic spatial analysis unit. Coupling subscribers’ footprints and urban places in physical space, the spatiotemporal visit patterns of urban places by distinct social groups are uncovered and interpreted by non‐negative matrix factorization. The proposed framework enables us to answer several critical questions from three perspectives: (1) How to model popular urban places in terms of vague boundary, land use, and semantic features based on crowdsourcing data?; (2) How to evaluate interaction between individuals for inspecting the relationship between spatial proximity and social ties based on spatiotemporal co‐occurrence?; and (3) How to distinguish urban place visit preferences for social groups associated with different socio‐demographic characteristics? Our research could assist urban planners and municipal managers to identify critical urban places frequented by different population groups according to their roles and social/cultural characteristics for improvement of urban facility allocation. Numéro de notice : A2020-767 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12654 Date de publication en ligne : 30/06/2020 En ligne : https://doi.org/10.1111/tgis.12654 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96658 [article]

Analyzing relatedness by toponym co-occurrences on web pages / Yu Liu in Transactions in GIS, vol 18 n° 1 (February 2014)  

Public [article]  inTransactions in GIS > vol 18 n° 1 (February 2014) . - pp 89 - 107 Titre : Analyzing relatedness by toponym co-occurrences on web pages Type de document : Article/Communication Auteurs : Yu Liu, Auteur ; Fahui Wang, Auteur ; Chaogui Kang, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 89 - 107 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse spatiale [Termes IGN] Chine [Termes IGN] données massives [Termes IGN] matrice de co-occurrence [Termes IGN] moteur de recherche [Termes IGN] objet géographique [Termes IGN] outil de découverte de connaissances [Termes IGN] relation topologique [Termes IGN] voisinage (relation topologique) Résumé : (Auteur) This research proposes a method for capturing “relatedness between geographical entities” based on the co-occurrences of their names on web pages. The basic assumption is that a higher count of co-occurrences of two geographical places implies a stronger relatedness between them. The spatial structure of China at the provincial level is explored from the co-occurrences of two provincial units in one document, extracted by a web information retrieval engine. Analysis on the co-occurrences and topological distances between all pairs of provinces indicates that: (1) spatially close provinces generally have similar co-occurrence patterns; (2) the frequency of co-occurrences exhibits a power law distance decay effect with the exponent of 0.2; and (3) the co-occurrence matrix can be used to capture the similarity/linkage between neighboring provinces and fed into a regionalization method to examine the spatial organization of China. The proposed method provides a promising approach to extracting valuable geographical information from massive web pages. Numéro de notice : A2014-066 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12011 Date de publication en ligne : 19/03/2013 En ligne : https://doi.org/10.1111/tgis.12011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32971 [article]