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Moving point object data can be analyzed through the discovery of patterns in trajectories. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounter, as defined by Laube et al., Finding REMO-detecting relative motion patterns in geospatial lifelines, 201-214, (2004). These patterns are large enough subgroups of the moving point objects that exhibit similar movement in the sense of direction, heading for thedoi:10.1007/s10707-006-0002-z fatcat:svcbdvqiovh6bht5ncz37w35em