Modeling and implement of mobile phone user location discrimination based on heuristic strategy
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...
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doaj-c25e7ceb393f4ae586b4edce014649462020-11-25T03:19:39ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992019-09-01201911910.1186/s13638-019-1535-9Modeling and implement of mobile phone user location discrimination based on heuristic strategyQingchao Shan0Honghui Dong1Limin Jia2Hua Yuan3Hui Zhang4School of Traffic and Transportation, Beijing Jiaotong UniversitySchool of Traffic and Transportation, Beijing Jiaotong UniversitySchool of Traffic and Transportation, Beijing Jiaotong UniversityBeijing MainSoft Technology Corporation LimitedTransportation and Economics Research Institute, China Academy of Railway Sciences Corporation LimitedAbstract 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.http://link.springer.com/article/10.1186/s13638-019-1535-9Location discriminationHeuristic strategyHandoverMobile phone dataCell oscillation phenomenonBig data mining |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qingchao Shan Honghui Dong Limin Jia Hua Yuan Hui Zhang |
spellingShingle |
Qingchao Shan Honghui Dong Limin Jia Hua Yuan Hui Zhang Modeling and implement of mobile phone user location discrimination based on heuristic strategy EURASIP Journal on Wireless Communications and Networking Location discrimination Heuristic strategy Handover Mobile phone data Cell oscillation phenomenon Big data mining |
author_facet |
Qingchao Shan Honghui Dong Limin Jia Hua Yuan Hui Zhang |
author_sort |
Qingchao Shan |
title |
Modeling and implement of mobile phone user location discrimination based on heuristic strategy |
title_short |
Modeling and implement of mobile phone user location discrimination based on heuristic strategy |
title_full |
Modeling and implement of mobile phone user location discrimination based on heuristic strategy |
title_fullStr |
Modeling and implement of mobile phone user location discrimination based on heuristic strategy |
title_full_unstemmed |
Modeling and implement of mobile phone user location discrimination based on heuristic strategy |
title_sort |
modeling and implement of mobile phone user location discrimination based on heuristic strategy |
publisher |
SpringerOpen |
series |
EURASIP Journal on Wireless Communications and Networking |
issn |
1687-1499 |
publishDate |
2019-09-01 |
description |
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. |
topic |
Location discrimination Heuristic strategy Handover Mobile phone data Cell oscillation phenomenon Big data mining |
url |
http://link.springer.com/article/10.1186/s13638-019-1535-9 |
work_keys_str_mv |
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1724620947112067072 |