Handbook of Mobility Data Mining, Volume One: Data Preprocessing and
Visualization introduces the fundamental technologies of mobile big
data mining (MDM), advanced AI methods, and upper-level applications,
helping readers comprehensively understand MDM with a bottom-up
approach. The book explains how to preprocess mobile big data, visualize
urban mobility, simulate and predict human travel behavior, and assess
urban mobility characteristics and their matching performance as
conditions and constraints in transport, emergency management, and
sustainability development systems. The book contains crucial
information for researchers, engineers, operators, administrators, and
policymakers seeking greater understanding of current technologies'
infra-knowledge structure and limitations.
Further, the book introduces how to design MDM platforms that adapt to
the evolving mobility environment, new types of transportation, and
users based on an integrated solution that utilizes sensing and
communication capabilities to tackle significant challenges faced by the
MDM field. This volume focuses on how to efficiently pre-process mobile
big data to extract and utilize critical feature information of
high-dimensional city people flow. The book first provides a conceptual
theory and framework, then discusses data sources, trajectory
map-matching, noise filtering, trajectory data segmentation, data
quality assessment, and more, concluding with a chapter on privacy
protection in mobile big data mining.
