PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Parent C., Spaccapietra S., Renso C., Andrienko G., Andrienko N., Bogorny V., Damiani M. L., Gkoulalas-Divanis A., Macedo J. A., Pelekis N., Theodoridis Y., Yan Z. Semantic trajectories modeling and analysis. In: Computing Surveys, vol. 45 (4) pp. 1 - 32. ACM, 2013.
 
 
Abstract
(English)
Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the article surveys the new privacy issues that arise due to the semantic aspects of trajectories.
URL: http://dl.acm.org/citation.cfm?id=2501656&CFID=359536952&CFTOKEN=71022417
DOI: 10.1145/2501654.2501656
Subject Semantic trajectory
Survey
Mobility analysis
H.2.8 Database Applications
68U99


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