| Summary: | Abstract With the all-pervading mobile devices and continuing advancement of big data technologies, mobile phone data research has been gaining widespread popularity in the past few years. Dealing with the implausible location caused by cell handover phenomenon in the communication system is one key problem of user mobility profile building based on mobile phone call detail records (CDRs) data. In this paper, we propose a location discrimination model aiming at CDRs data, where heuristic strategies for the characteristic of the oscillation phenomenon from practical CDRs and handover categories are added to distinguish the stay points, passing points, and oscillating points. A whole month of CDRs data from one communication operator is employed to select parameters and validate the model on the Spark platform. The experiment results betray that the proposed model can identify the false locations effectively. Compared with the threshold models, the result of the proposed model is more reasonable both in the population aggregate level and individual level. Besides, the model can retain more user’s trajectory points than clustering algorithm, so it can improve the quality of user mobility modeling.
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