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dc.contributor.authorLin, Yi-Bingen_US
dc.contributor.authorHuang-Fu, Chien-Chunen_US
dc.contributor.authorAlrajeh, Nabilen_US
dc.date.accessioned2014-12-08T15:30:35Z-
dc.date.available2014-12-08T15:30:35Z-
dc.date.issued2013-06-01en_US
dc.identifier.issn1536-1233en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TMC.2012.87en_US
dc.identifier.urihttp://hdl.handle.net/11536/21861-
dc.description.abstractInvestigating human movement behavior is important for studying issues such as prediction of vehicle traffic and spread of contagious diseases. Since mobile telecom network can efficiently monitor the movement of mobile users, the telecom's mobility management is an ideal mechanism for studying human movement issues. The problem can be abstracted as follows: What is the probability that a person at location A will move to location B after T hours. The answer cannot be directly obtained because commercial telecom networks do not exactly trace the movement history of every mobile user. In this paper, we show how to use the standard outputs (handover rates, call arrival rates, call holding time, and call traffic) measured in a mobile telecom network to derive the answer for this problem.en_US
dc.language.isoen_USen_US
dc.subjectHuman movementen_US
dc.subjectLittle's Lawen_US
dc.subjectmobile computingen_US
dc.subjectmobility managementen_US
dc.titlePredicting Human Movement Based on Telecom's Handoff in Mobile Networksen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TMC.2012.87en_US
dc.identifier.journalIEEE TRANSACTIONS ON MOBILE COMPUTINGen_US
dc.citation.volume12en_US
dc.citation.issue6en_US
dc.citation.spage1236en_US
dc.citation.epage1241en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000319409900016-
dc.citation.woscount2-
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