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Connecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. / Caglar Koylu in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 12 (December 2021) . - pp 2380 - 2423 Titre : Connecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur ; Diansheng Guo, Auteur ; Yuan Huang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2380 - 2423 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] appariement sémantique [Termes IGN] collecte de données [Termes IGN] démographie [Termes IGN] dix-neuvième siècle [Termes IGN] données localisées des bénévoles [Termes IGN] données publiques [Termes IGN] Etats-Unis [Termes IGN] généalogie [Termes IGN] géocodage [Termes IGN] historique des données [Termes IGN] itération [Termes IGN] migration humaine [Termes IGN] mobilité humaine [Termes IGN] réseau social géodépendant [Termes IGN] système d'information historique Résumé : (auteur) We collected 92,832 user-contributed and publicly available family trees from rootsweb.com, including 250 million individuals who were born in North America and Europe between 1630 and 1930. We cleaned and connected the family trees to create a population-scale and longitudinal family tree dataset using a workflow of data collection and cleaning, geocoding, fuzzy record linkage and a relation-based iterative search for connecting trees and deduplication of records. Given the largest connected component of nearly 40 million individuals, and a total of 80 million individuals, we generated, to date, the largest population-scale and longitudinal geo-social network over centuries. We evaluated the representativeness of the family tree dataset for historical population demography and mobility by comparing the data to the 1880 Census. Our results showed that the family trees were biased towards males, the elderly, farmers, and native-born white segments of the population. Individuals were highly mobile – in our 1880 sample of parent-child pairs where both were born in the U.S., 47% were born in different states. Our findings agreed with prior studies that people migrated from East to West in horizontal bands, and the trend was reflected in the dialects and regional structure of the U.S. Numéro de notice : A2021-876 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1821885 Date de publication en ligne : 30/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1821885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99139 [article]

Mapping large spatial flow data with hierarchical clustering / Xi Zhu in Transactions in GIS, vol 18 n° 3 (June 2014)  

Public [article]  inTransactions in GIS > vol 18 n° 3 (June 2014) . - pp 421 - 435 Titre : Mapping large spatial flow data with hierarchical clustering Type de document : Article/Communication Auteurs : Xi Zhu, Auteur ; Diansheng Guo, Auteur Année de publication : 2014 Article en page(s) : pp 421 - 435 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] analyse de groupement [Termes IGN] cartographie des flux [Termes IGN] classification ascendante hiérarchique [Termes IGN] données de flux [Termes IGN] index spatial [Termes IGN] segmentation sémantique [Termes IGN] zone urbaine Résumé : (Auteur) It is challenging to map large spatial flow data due to the problem of occlusion and cluttered display, where hundreds of thousands of flows overlap and intersect each other. Existing flow mapping approaches often aggregate flows using predetermined high-level geographic units (e.g. states) or bundling partial flow lines that are close in space, both of which cause a significant loss or distortion of information and may miss major patterns. In this research, we developed a flow clustering method that extracts clusters of similar flows to avoid the cluttering problem, reveal abstracted flow patterns, and meanwhile preserves data resolution as much as possible. Specifically, our method extends the traditional hierarchical clustering method to aggregate and map large flow data. The new method considers both origins and destinations in determining the similarity of two flows, which ensures that a flow cluster represents flows from similar origins to similar destinations and thus minimizes information loss during aggregation. With the spatial index and search algorithm, the new method is scalable to large flow data sets. As a hierarchical method, it generalizes flows to different hierarchical levels and has the potential to support multi-resolution flow mapping. Different distance definitions can be incorporated to adapt to uneven spatial distribution of flows and detect flow clusters of different densities. To assess the quality and fidelity of flow clusters and flow maps, we carry out a case study to analyze a data set of 243,850 taxi trips within an urban area. Numéro de notice : A2014-273 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12100 Date de publication en ligne : 26/05/2014 En ligne : https://doi.org/10.1111/tgis.12100 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33176 [article]

vol 33 n°6 - November 2009 - Spatial data mining-methods and applications (Bulletin de Computers, Environment and Urban Systems) / Diansheng Guo  

Public [n° ou bulletin]  Titre : vol 33 n°6 - November 2009 - Spatial data mining-methods and applications Type de document : Périodique Auteurs : Diansheng Guo, Auteur ; Jeremy Mennnis, Auteur Année de publication : 2009 Langues : Anglais (eng) Numéro de notice : 239-0906 Affiliation des auteurs : non IGN Nature : Numéro de périodique En ligne : http://www.sciencedirect.com/science/journal/01989715/33/6 Format de la ressource électronique : URL Sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=26467 [n° ou bulletin]