Find Your Way Back: Mobility Profile Mining with Constraints

Contributing Authors: 
  • Lars Kotthoff
Additional Credits: 
  • Mirco Nanni

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.

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