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.).
|Original language||English (US)|
|Title of host publication||Wireless Networks(United Kingdom)|
|Publisher||Springer Science and Business Media B.V.|
|Number of pages||20|
|State||Published - 2018|
|Name||Wireless Networks(United Kingdom)|
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