A weighted combination similarity measure for mobility patterns in
  wireless networks
  The similarity between trajectory patterns in clustering has played an
important role in discovering movement behaviour of different groups of mobile
objects. Several approaches have been proposed to measure the similarity
between sequences in trajectory data. Most of these measures are based on
Euclidean space or on spatial network and some of them have been concerned with
temporal aspect or ordering types. However, they are not appropriate to
characteristics of spatiotemporal mobility patterns in wireless networks. In
this paper, we propose a new similarity measure for mobility patterns in
cellular space of wireless network. The framework for constructing our measure
is composed of two phases as follows. First, we present formal definitions to
capture mathematically two spatial and temporal similarity measures for
mobility patterns. And then, we define the total similarity measure by means of
a weighted combination of these similarities. The truth of the partial and
total similarity measures are proved in mathematics. Furthermore, instead of
the time interval or ordering, our work makes use of the timestamp at which two
mobility patterns share the same cell. A case study is also described to give a
comparison of the combination measure with other ones.
