Xiang Cheng, Luoyang Fang, Liuqing Yang, Shuguang Cui

Research output: Chapter in Book/Report/Conference proceedingChapter


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 languageEnglish (US)
Title of host publicationWireless Networks(United Kingdom)
PublisherSpringer Science and Business Media B.V.
Number of pages20
StatePublished - 2018
Externally publishedYes

Publication series

NameWireless Networks(United Kingdom)
ISSN (Print)2366-1186
ISSN (Electronic)2366-1445

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.


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