Sequential Formal Concepts over Time for Trajectory Analysis

Feda Almuhisen (1) , Nicolas Durand (1) , Mohamed Quafafou (1)

1 DANA - Data Mining at scale

Tracking technologies and location-acquisition have led to the increase of the availability of trajectory data. Many efforts are devoted to develop methods for mining and analysing trajectories due to its importance in lots of applications such as traffic control, urban planning etc. In this paper, we present a new trajectory analysis and visualisation framework for massive movement data. This framework leverages formal concepts, sequential patterns, emerging patterns, and analyses the evolution of mobility patterns through time. Tagged city maps are generated to display the resulting evolution analysis and directions at different spatio-temporal granularity values. Experiments on real-world dataset show the relevance of the proposition and the usefulness of the resulting tagged city maps.

Mots clés: Concept lattice; Visualization; Sequential patterns; Trajectories; Spatio-temporal data

Domaines: Autre [cs.OH]; Informatique

Feda Almuhisen, Nicolas Durand, Mohamed Quafafou. Sequential Formal Concepts over Time for Trajectory Analysis. IEEE/WIC/ACM International Conference on Web Intelligence (WI 2018), Dec 2018, Santiago, Chile. ⟨hal-01952227⟩