基于Cell-id的移动数据精确定位捕获
Precise Location Acquisition of Mobility Data Using Cell-id
摘要：
这篇论文已被作者撤回。蜂窝网络数据已成为提取用户移动性和时空趋势的研究热点。移动数据中的位置绑定可以通过不同的方法来完成，如GPS、服务提供商辅助的伪GPS和小区全球身份（CGI）。在这些方法中，小区全球身份是最便宜的方法和现成的解决方案的移动性提取，但精确的空间提取是在某种程度上是一个问题。本文提出的空间提取技术的移动电话用户的原始数据，其中携带的信息，如位置信息，邻近位置和活动的主题。本工作主要集中在数据预处理的方法和技术，解释低级别的移动性数据到高级别的移动性信息，使用设计的聚类方法和可获得的Cell-ID数据库。工作提出了半监督的策略，通过使用语义标签信息和删除空间离群点来获得缺失位置，以精确构建移动性剖面。
英文摘要：
This paper has been withdrawn by the authors. Cellular network data has become a hot source of study for extraction of user-mobility and spatio-temporal trends. Location binding in mobility data can be done through different methods like GPS, service provider assisted faux-GPS and Cell Global Identity (CGI). Among these Cell Global Identity is most inexpensive method and readily available solution for mobility extraction; however exact spatial extraction is somehow a problem in it. This paper presents the spatial extraction technique of mobile phone user raw data which carries the information like location information, proximity location and activity of subjects. This work mainly focuses on the data pre-processing methodology and technique to interpret the low level mobility data into high level mobility information using the designed clustering methodology and publically available Cell-IDs databases. Work proposed the semi- supervised strategy to derive the missing locations thorough the usage of semantic tag information and removal of spatial outliers for precise mobility profile building.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
