期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：3
出版社：IJCSI Press
摘要：Mobility profile building became extensively examined area in Location based services (LBS) through extraction of significant locations. Mobility traces are recorded under three reference positioning systems that are Satellite based i.e. GPS, Network based i.e. GSM and Local positioning i.e. WLAN, RFID, IrDA. Satellite based and local positioning due to of high power consumption, additional resource installation, low accuracy and space limitation are less encouraging. So network based positioning i.e. GSM is only viable solution for mobility tracing through Cell global identity (CGI). CGI presents the Cell-ids to extract the significant locations from mobility history. However CGI faces cell oscillation problem, where user is assigned multiple Cell-Ids even at a stationary state for load balancing and GSM cells overlapping. In this paper we proposed two semi-supervised methodology for cell oscillation resolution i.e. semantic tagging and overlapped area clustering, the proposed methodologies are equally useful for the identification of significant places too.
