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Kotthoff L., Nanni M., Guidotti R., O'Sullivan B. Find your way back: mobility profile mining with constraints. In: CP 2015 - Principles and Practice of Constraint Programming. 21st International Conference (Cork, Ireland, 31 August - 4 September 2015). Proceedings, pp. 638 - 653. Gilles Pesant (ed.). (Lecture Notes in Computer Science, vol. 9255). Springer, 2015.
 
 
Abstract
(English)
Mobility profile mining is a data mining task that can be formulated as clustering over movement trajectory data. The main challenge is to separate the signal from the noise, i.e. one-off trips. We show that standard data mining approaches suffer the important drawback that they cannot take the symmetry of non-noise trajectories into account. That is, if a trajectory has a symmetric equivalent that covers the same trip in the reverse direction, it should become more likely that neither of them is labelled as noise. We present a constraint model that takes this knowledge into account to produce better clusters. We show the efficacy of our approach on real-world data that was previously processed using standard data mining techniques.
URL: http://link.springer.com/chapter/10.1007/978-3-319-23219-5_44
DOI: 10.1007/978-3-319-23219-5_44
Subject Clustering Trajectories
Constraint Programming
Individual Mobility Profiles
H.2.8 Database Applications. Data Mining
68W01


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