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Giannotti, Fosca; Pedreschi, Dino (Eds.)
2008, XIV, 410 p. 96 illus., 12 in color., Hardcover
ISBN: 978-3-540-75176-2
About this book
The technologies of mobile communications and ubiquitous computing pervade our society, and wireless networks sense the movement of people and vehicles, generating large volumes of mobility data. This is a scenario of great opportunities and risks: on one side, mining this data can produce useful knowledge, supporting sustainable mobility and intelligent transportation systems; on the other side, individual privacy is at risk, as the mobility data contain sensitive personal information. A new multidisciplinary research area is emerging at this crossroads of mobility, data mining, and privacy.
This book assesses this research frontier from a computer science perspective, investigating the various scientific and technological issues, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, funded by the EU Commission and involving 40 researchers from 7 countries, and this book tightly integrates and relates their findings in 13 chapters covering all related subjects, including the concepts of movement data and knowledge discovery from movement data; privacy-aware geographic knowledge discovery; wireless network and next-generation mobile technologies; trajectory data models, systems and warehouses; privacy and security aspects of technologies and related regulations; querying, mining and reasoning on spatiotemporal data; and visual analytics methods for movement data.
This book will benefit researchers and practitioners in the related areas of computer science, geography, social science, statistics, law, telecommunications and transportation engineering.
Written for:
Researchers and professionals
Keywords:
Data Mining Geographic Knowledge Discovery Mobility Privacy Spatio-temporal Data Mining Trajectory Data Models Trajectory Data Warehouses Trajectory Database Systems Wireless Networks
Springer Mobility Data Mining And Privacy Jan 2008.pdf
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