Ambiguity and plausibility: Managing classification quality in volunteered geographic information

GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Volumn 04-07-November-2014, Issue , 2014, Pages 143-152

  Ali, Ahmed Loai ^a,b   Schmid, Falko ^a   Al Salman, Rami ^a   Kauppinen, Tomi ^a,c  

^a UNIVERSITY OF BREMEN   (Germany)

^b Assiut University   (Egypt)

^c AALTO UNIVERSITY   (Finland)

Author keywords

Geographic Information Systems; Machine Learning; Spatial Data Quality; Volunteered Geographic Information

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SOFTWARE MAINTENANCE; GEOGRAPHIC INFORMATION SYSTEMS; INFORMATION SYSTEMS; LEARNING SYSTEMS;

CLASSIFICATION QUALITY; DATA QUALITY; DETECTION ACCURACY; GEO-SPATIAL DATA; SPATIAL DATA QUALITY; TRAINING DATA; USER AGREEMENTS; VOLUNTEERED GEOGRAPHIC INFORMATION;

CLASSIFICATION (OF INFORMATION);

EID: 84961211333     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2666310.2666392     Document Type: Conference Paper

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