移动性轮廓建立中的小区振荡解决方案
Cell Oscillation Resolution in Mobility Profile Building
摘要：
这篇论文已被作者撤回。通过提取重要位置，移动性配置文件的建立成为基于位置的服务（LBS）中广泛研究的领域。在三个参考定位系统下记录移动轨迹，这三个参考定位系统是基于卫星的即GPS、基于网络的即GSM和本地定位即WLAN、RFID、IrDA。基于卫星的定位和本地定位由于高功耗、额外的资源安装、低精度和空间限制而不太令人鼓舞。因此，基于网络的定位，即GSM是通过小区全球身份（CGI）进行移动性跟踪的唯一可行的解决方案。CGI提供Cell-id以从移动历史中提取重要位置。然而，CGI面临小区振荡问题，其中用户即使在静止状态下也被分配多个Cell-Id以用于负载均衡和GSM小区重叠。在本文中，我们提出了两个半监督的方法来解决细胞振荡，即语义标记和重叠区域聚类，所提出的方法是同样有用的重要地点的识别。
英文摘要：
This paper has been withdrawn by the authors. 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.
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