Mining Trajectory Data and Geotagged Data in Social Media for Road Map Inference
- Li, Jun
- Qin, Qiming
- Han, Jiawei
- Tang, Lu-An
- Lei, Kin Hou
DOIAbstract
As mapping is costly and labor-intensive work, government mapping agencies are less and less willing to absorb these costs. In order to reduce the updating cycle and cost, researchers have started to use user generated content (UGC) for updating road maps; however, the existing methods either rely heavily on manual labor or cannot extract enough information for road maps. In view of the above problems, this article proposes a UGC-based automatic road map inference method. In this method, data mining techniques and natural language processing tools are applied to trajectory data and geotagged data in social media to extract not only spatial information - the location of the road network - but also attribute information - road class and road ...
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