{"title":"收集和分析来自移动网络的移动数据","authors":"Yanfeng Weixiong Zhu Shang, Zhou Jin, Ying Chun","doi":"10.1109/ICBNMT.2009.5347791","DOIUrl":null,"url":null,"abstract":"Collecting and analyzing massive mobility data from mobile network is becoming an emerging research topic in past years. It is proved to have great potential in lots of domains, e.g. intelligence traffic system, urban analysis, public safety etc. However, due to variety of data collection mechanisms, the data characteristics are various and need to be abstracted. In this paper, we outline the mobility data collection approaches and identify the differentiation in data characteristics and data process requirements. Then we propose an extendable framework which provides general data abstraction and universal data process flow for various mobility data. The experiment results are also presented to prove the framework.","PeriodicalId":267128,"journal":{"name":"2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Collecting and analyzing mobility data from mobile network\",\"authors\":\"Yanfeng Weixiong Zhu Shang, Zhou Jin, Ying Chun\",\"doi\":\"10.1109/ICBNMT.2009.5347791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Collecting and analyzing massive mobility data from mobile network is becoming an emerging research topic in past years. It is proved to have great potential in lots of domains, e.g. intelligence traffic system, urban analysis, public safety etc. However, due to variety of data collection mechanisms, the data characteristics are various and need to be abstracted. In this paper, we outline the mobility data collection approaches and identify the differentiation in data characteristics and data process requirements. Then we propose an extendable framework which provides general data abstraction and universal data process flow for various mobility data. The experiment results are also presented to prove the framework.\",\"PeriodicalId\":267128,\"journal\":{\"name\":\"2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBNMT.2009.5347791\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd IEEE International Conference on Broadband Network & Multimedia Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBNMT.2009.5347791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Collecting and analyzing mobility data from mobile network
Collecting and analyzing massive mobility data from mobile network is becoming an emerging research topic in past years. It is proved to have great potential in lots of domains, e.g. intelligence traffic system, urban analysis, public safety etc. However, due to variety of data collection mechanisms, the data characteristics are various and need to be abstracted. In this paper, we outline the mobility data collection approaches and identify the differentiation in data characteristics and data process requirements. Then we propose an extendable framework which provides general data abstraction and universal data process flow for various mobility data. The experiment results are also presented to prove the framework.