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Mobile Big Data pp 51–70Cite as

Applications

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Abstract

Analytics and mining over mobile big data enriched with time and location information will provide great opportunities for new services. The potential applications driven by such mobile user data could be roughly divided into two categories. One is mining on the individual user data to provide personalized services (e.g., context-aware sensing, point of interests, activity recognition, etc.). The other is mining on the aggregation of mobile user data to learn and analyze the pattern of human activities, which aims to understand human behaviors in order to help public service planning and city management (e.g., social response monitoring in lieu of social events or disasters, anomaly detection, traffic flow pattern learning, city zone characterization, etc.).

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Authors and Affiliations

  1. State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics Engineering and Computing Science, Peking University, Beijing, China

    Xiang Cheng

  2. Department of Electrical & Computing Engineering, Colorado State University, Fort Collins, CO, USA

    Luoyang Fang & Liuqing Yang

  3. Department of Electrical and Computer Engineering, University of California - Davis, Davis, CA, USA

    Shuguang Cui

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  1. Xiang Cheng
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Cheng, X., Fang, L., Yang, L., Cui, S. (2018). Applications. In: Mobile Big Data. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-96116-3_5

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