Precise Location Acquisition of Mobility Data Using Cell ID
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.
Keywords: Mobility data, Spatial extraction, Trajectory mining, GSM network
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ABOUT THE AUTHORS
Shafqat Ali Shad
Mr. Shafqat Ali Shad is second year doctoral student at USTC. He obtained his Master degree in Computer Science from COMSATS Institute of Information Technology, Pakistan with the distinction of Chancellor Gold Medal in 2004. He had worked as National ICT Consultant for Asian Development Bank for Health sector reforms program in Pakistan mainly focused on Pakistan millennium development goals in 2010. He also worked with Planning Commission, Government of Pakistan as Deputy Director for ICT policy making and implementation of Five year plans, Annual plans and Vision 2030 from 2004 to 2009. Beside this He worked as freelance ERP consultant for SAP and Oracle E-business suite implementations in large enterprises for almost 5 years. His professional certifications include Oracle 10g DBA, Juniper Certified Internet Specialist-ER and PMP. His current research interests include Mobile mining, Recommender systems, Machine learning and ERP systems. He is the author of 3 international journal publications.
Enhong Chen
Dr. Chen Enhong, born in July 1968, currently works as a professor and doctoral supervisor at the Laboratory of Semantic Computing and Data Mining, University of Science and Technology of China (USTC). Prof. Chen is also a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). Chen obtained his Ph.D. in Computer Software from USTC. Prof. Chen currently serves as Vice Dean of School of Computer Science and Technology of China, Deputy Director of the MOE–Microsoft Key Laboratory of Multimedia Computing and Communication, University of Science and Technology of China, Member of the Knowledge Engineering Committee and the Machine Learning Committee of the Chinese Association for Artificial Intelligence, Member of the Artificial Intelligence and Pattern Recognition Committee of the China Computer Federation. Besides, Prof. Chen also serves on the program committees for over 20 international academic conferences.Prof. Chen has authored more than 90 research papers and invited papers published in international and domestic academic journals or submitted to international academic conferences. His paper presented to the top international conference on data mining, namely, the KDD2008, has won the Best Application Paper Award.
Shafqat Ali Shad
Mr. Shafqat Ali Shad is second year doctoral student at USTC. He obtained his Master degree in Computer Science from COMSATS Institute of Information Technology, Pakistan with the distinction of Chancellor Gold Medal in 2004. He had worked as National ICT Consultant for Asian Development Bank for Health sector reforms program in Pakistan mainly focused on Pakistan millennium development goals in 2010. He also worked with Planning Commission, Government of Pakistan as Deputy Director for ICT policy making and implementation of Five year plans, Annual plans and Vision 2030 from 2004 to 2009. Beside this He worked as freelance ERP consultant for SAP and Oracle E-business suite implementations in large enterprises for almost 5 years. His professional certifications include Oracle 10g DBA, Juniper Certified Internet Specialist-ER and PMP. His current research interests include Mobile mining, Recommender systems, Machine learning and ERP systems. He is the author of 3 international journal publications.
Enhong Chen
Dr. Chen Enhong, born in July 1968, currently works as a professor and doctoral supervisor at the Laboratory of Semantic Computing and Data Mining, University of Science and Technology of China (USTC). Prof. Chen is also a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). Chen obtained his Ph.D. in Computer Software from USTC. Prof. Chen currently serves as Vice Dean of School of Computer Science and Technology of China, Deputy Director of the MOE–Microsoft Key Laboratory of Multimedia Computing and Communication, University of Science and Technology of China, Member of the Knowledge Engineering Committee and the Machine Learning Committee of the Chinese Association for Artificial Intelligence, Member of the Artificial Intelligence and Pattern Recognition Committee of the China Computer Federation. Besides, Prof. Chen also serves on the program committees for over 20 international academic conferences.Prof. Chen has authored more than 90 research papers and invited papers published in international and domestic academic journals or submitted to international academic conferences. His paper presented to the top international conference on data mining, namely, the KDD2008, has won the Best Application Paper Award.
