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Automatic Tag Enrichment for Points-of-Interest in Open Street Map
6 references·1 citing·27 second hop
Automatic Tag Enrichment for Points-of-Interest in Open Street Map (2017)Automatic Tag Enrichment for Points-of-In…OSMRec Tool for Automatic Recommendation of Categories on Spatial Entities in OpenStreetMap (2015)OSMRec Tool for Automatic Rec…Quality assessment for building footprints data on OpenStreetMap (2014)Quality assessment for buildi…Multi-granular Street Network Representation towards Quality Assessment of OpenStreetMap Data (2013)Multi-granular Street Network…Mining urban land-use patterns from volunteered geographic information by means of genetic algorithms and artificial neural networks (2011)Mining urban land-use pattern…Quality Assessment of the French OpenStreetMap Dataset (2010)Quality Assessment of the Fre…How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets (2010)How Good is Volunteered Geogr…A Semantically Enhanced Label Prediction Method for Imbalanced POI Data Category Distribution (2024)A Semantically Enhanced Label…Citizens as Voluntary Sensors: Spatial Data Infrastructure in the World of Web 2.0 (2007)A review of volunteered geographic information quality assessment methods (2016)The world’s user-generated road map is more than 80% complete (2017)Global maps of travel time to healthcare facilities (2020)A Computer Movie Simulating Urban Growth in the Detroit Region (1970)Citizens as sensors: the world of volunteered geography (2007)OpenStreetMap: User-Generated Street Maps (2008)An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications (2015)Mapping and the Citizen Sensor (2017)Volunteered geographic information research in the first decade: a narrative review of selected journal articles in GIScience (2020)Assuring the quality of volunteered geographic information (2012)Probabilistic Graphical Modelling for Semantic Labelling of Crowdsourced Map Data (2015)BITOUR: A Business Intelligence Platform for Tourism Analysis (2020)Developing a multi-classifier system to classify OSM tags based on centrality parameters (2021)Automated highway tag assessment of OpenStreetMap road networks (2014)Freedom versus Standardization (2017)Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM (2021)How Many Volunteers Does it Take to Map an Area Well? The Validity of Linus’ Law to Volunteered Geographic Information (2010)MEASURES AND INDICATORS OF VGI QUALITY: AN OVERVIEW (2015)OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing (2020)A spatio-temporal analysis investigating completeness and inequalities of global urban building data in OpenStreetMap (2023)The world is flat: a brief history of the twenty-first century (2006)Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice (2011)Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation (2012)How where is when? On the regional variability and resolution of geosocial temporal signatures for points of interest (2015)Identifying spatiotemporal urban activities through linguistic signatures (2018)Visualizing and exploring POI configurations of urban regions on POI-type semantic space (2020)
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References

  • 2010How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets1,640 cited
  • 2010Quality Assessment of the French OpenStreetMap Dataset668 cited
  • 2014Quality assessment for building footprints data on OpenStreetMap423 cited
  • 2011Mining urban land-use patterns from volunteered geographic information by means of genetic algorithms and artificial neural networks121 cited
  • 2013Multi-granular Street Network Representation towards Quality Assessment of OpenStreetMap Data24 cited
  • 2015OSMRec Tool for Automatic Recommendation of Categories on Spatial Entities in OpenStreetMap22 cited

Cited by

  • 2024A Semantically Enhanced Label Prediction Method for Imbalanced POI Data Category Distribution6 cited

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