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Communication Dans Un Congrès Année : 2018

Map Change Prediction for Quality Assurance Map Change Prediction for Quality Assurance

Résumé

Open geospatial datasources like OpenStreetMap are created by a community of mappers of different experience and with different equipment available. It is therefore important to assess the quality of Open-StreetMap-like maps to give recommendations for users in which situations a map is suitable for their needs. In this work we want to use already defined ways to assess the quality of geospatial data and apply them to a Machine Learning algorithm to classify which areas are likely to change in future revisions of the map. In a next step we intend to qualify the changes detected by the algorithm and try to find causes of the changes being tracked.
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Dates et versions

hal-02289169 , version 1 (16-09-2019)

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Timo Homburg, Frank Boochs, Christophe Cruz, Ana-Maria Roxin. Map Change Prediction for Quality Assurance Map Change Prediction for Quality Assurance. 14th International Conference on Location Based Services, Jan 2018, Zurich, Switzerland. ⟨10.3929/ethz-b-000225617⟩. ⟨hal-02289169⟩
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