Abstract
The use of traditional positioning technologies, such as GPS and wireless local positioning, rely on underlying infrastructure. However, in a subway environment, such positioning systems are not available for the positioning tasks, such as the detection of the train arrivals for the passengers in the train. An alternative approach is to exploit the contextual information available in the mobile devices of subway riders to detect train arrivals. To this end, we propose to exploit multiple contextual features extracted from the mobile devices of subway riders to precisely detecting train arrivals. Following this line, we first investigate potential contextual features which may be effective to detect train arrivals according to the observations from 3D accelerometers and GSM radio. Furthermore, we propose to explore the maximum entropy (MaxEnt) model for training a train arrival detector by learning the correlation between contextual features and train arrivals. Finally, we perform extensive experiments on several real-world data sets collected from two major subway lines in the Beijing subway system. Experimental results validate both the effectiveness and efficiency of the proposed approach.
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This is a substantially extended and revised version of our earlier work [1], which appears in the Proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL’13).
Kuifei Yu is a director of Invention Research and Development in Zhigu.com. He is a PhD candidate in the University of Chinese Academy of Sciences, Beijing, China. He received his BS from North China University of Water Resources and Electric Power, China in 2004, and his MS from Beijing University of Posts and Telecommunications, China in 2007, both in Computer Science and Technology. He joined Nokia Research Center as a researcher, then senior researcher during 2007 and 2012. His current research interests include mobile data mining, computational advertising, and patent mining. In these fields, he has applied around 30 invention patents world wide and published several papers in refereed conference proceedings and journals, such as PAKDD, ICDM, and TIST.
Hengshu Zhu is a PhD student in the School of Computer Science and Technology at the University of Science and Technology of China, Hefei. He was supported by the China Scholarship Council as a visiting research student at Rutgers-the State University of New Jersey, NJ, USA. He received his BE in Computer Science in 2009 from USTC.His main research interests include mobile data mining, intelligent data analysis, and social networks. He has published several papers in refereed conference proceedings and journals, such as CIKM, ICDM, and www Journal. He has been a journal reviewer for TSMC-B, www Journal and KAIS, and an external reviewer for several international conferences.
Huanhuan Cao is currently the principal scientist of Nuomi.com. Before joining Nuomi, he was a key research engineer of Hipu Info. Tech. Ltd, a start-up focusing on personalized news recommendation. Previously he worked for Nokia Research Center as a senior researcher. He received his BE and PhD from the University of Science and Technology of China, in 2005 and 2009, respectively. He won the Microsoft Fellow and Chinese Academic Science President Award. His current major research interests include recommender systems, location mining, and mobile user behavior analysis. In these fields, he has applied for more than 30 invention patents and published more than 20 papers in high rated conferences and journals.
Baoxian Zhang is a Full Professor of the University of Chinese Academy of Sciences, Beijing, China. He received his BS, MS, PhD degrees in Electrical Engineering from Northern Jiaotong University (Now Beijing Jiaotong University), China in 1994, 1997, and 2000, respectively. He has served as Guest Editors of special issues for ACM Mobile Networks and Applications and IEEE Journal on Selected Areas in Communications. He has served and continued to serve on technical program committees for many international conferences and symposia, including IEEE GLOBECOM, ICC, and WCNC. He has published over 100 refereed technical papers in archival journals and conference proceedings. His research interests cover network architecture, protocol and algorithm design, wireless ad hoc and sensor networks, and performance evaluation. He is a senior member of the IEEE.
Enhong Chen is Professor and Vice Dean of the School of Computer Science at University of Science and Technology of China. He received his PhD in Computer Science from the University of Science and Technology of China in 1996. His general area of research is web search and data mining, with a focus on developing effective and efficient data analysis techniques for emerging data intensive applications. He has published around 100 papers in refereed journals and conference proceedings. He is a senior member of the IEEE, and a member of the ACM.
Jilei Tian is a research leader in Nokia. He received his BS and MS in Biomedical Engineering from Xi’an Jiaotong University, China and his PhD in Computer Science from the University of Eastern Finland in 1985, 1988, and 1997, respectively. He was a faculty member of Beijing Jiaotong University, China from 1988 to 1994. He joined Nokia Research Center as senior researcher in 1997, primarily in the area of spoken language processing and recently in rich context data modeling and personalized services. He has authored more than 100 publications including book chapters, journals, and conference papers. He has also around 100 patents including those pending. He has served as a member of technical committees and on the editorial board of international conferences and journals.
Jinghai Rao is a senior staff engineer at Samsung Information Systems America. Before joining Samsung, he worked in Nokia, AOL, and Carnegie Mellon University, USA. He has more than 10 years research experience in ontology, semantic web, query expansion, context awareness and locationbased services. Dr. Rao is active in the artificial intelligence and knowledge representation research community. He has authored more than 30 scientific publications, and served as a program committee member or reviewer for various international conferences and journals. Dr. Rao received his PhD from Norwegian University of Science and Technology, Norway, and his MS and BS from Renmin University of China.
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Yu, K., Zhu, H., Cao, H. et al. Learning to detect subway arrivals for passengers on a train. Front. Comput. Sci. 8, 316–329 (2014). https://doi.org/10.1007/s11704-014-3258-8
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DOI: https://doi.org/10.1007/s11704-014-3258-8