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.
Highlights
Mobile phones have become ubiquitous devices in the world
Call detail records (CDRs) from mobile phones contain spatial-temporal of anonymized subscribers
Since CDRs are automatically collected by cell phone carriers for billing purposes, compared with data from traditional manual survey, mobile phone data have advantages in effortless collection, large-scale data, wide coverage, low collection cost, and good real-time performance, which have been studied largely in the transportation field, but it causes many challenges to be studied in depth [1, 2]
Summary
Mobile phones have become ubiquitous devices in the world. Each mobile phone connecting to the cellular network (GSM, CDMA, GPRS, UMTS, LTE, and so forth) generates digital traces which may serve as representative of traffic indicators and human behavior. González et al [3] analyzed human movement pattern based on mobile phone base station data and concluded. Despite these advantages, handover problem is very challenging because the mobile device’s real location is not known. In order to ensure that mobile station is connected to communication base station while it is stationary or moving, necessary handover should be implemented in mobile communication system [1, 12]. Geographical environment and buildings impact signal transmission, and overlap and load balancing in cellular signal coverage areas cause a mobile phone to be assigned to multiple base stations. The aim of this paper is to detect and alleviate trajectory distortion problem by heuristic strategies, so that the accuracy of path reconstruction can be improved in the position data provided by mobile operators
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