Extracting Social Web from Moving Object Trajectories
Jian Ming Dai · Applied Mechanics and Materials · 2013
The advent of a lot of mobile social networking applications on the smart phones has greatly changed the way how people interact with each other. The core function requiring by these applications is the location-based service providing by the sensors inside the phones. Accumulating rich location sequences, the phone actually can tell more than merely the location information. In this paper, we try to discover the beneath social web from these location information. In other words, we propose a novel trajectory mining approach to dig the social web from collections of such location information. Such approach permits to perform relationship mining from trajectory-generated content. Given a temporal threshold and a spatial threshold, our approach carries out trajectory based mining to identify who are in closer relationship with the querying moving object. The comprehensive evaluation of the approach has demonstrated very promising results and is also analyzed in this paper.