Similarity Search in Trajectory Databases
TIME '07 Proceedings of the 14th International Symposium on Temporal Representation and Reasoning
Visually driven analysis of movement data by progressive clustering
Information Visualization
Unsupervised trajectory sampling
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Exploring real mobility data with M-atlas
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
A clustering-based visualization of colocation patterns
Proceedings of the 15th Symposium on International Database Engineering & Applications
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In this paper we propose a demo of a Visual Analytics Toolkit to cope with the complexity of analysing a large dataset of moving objects, in a step wise manner. We allow the user to sample a small subset of objects, that can be handled in main memory, and to perform the analysis on this small group by means of a density based clustering algorithm. The GUI is designed in order to exploit and facilitate the human interaction during this phase of the analysis, to select interesting clusters among the candidates. The selected groups are used to build a classifier that can be used to label other objects from the original dataset. The classifier can then be used to efficiently associate all objects in the database to clusters. The tool has been tested using a large set of GPS tracked cars.