On-line location prediction exploiting spatial and velocity context

Anagnostopoulos, T., Anagnostopoulos, C. , Hadjiefthymiades, S. and Zaslavsky, A. (2015) On-line location prediction exploiting spatial and velocity context. International Journal of Wireless Information Networks, 22(1), pp. 29-40. (doi: 10.1007/s10776-014-0259-3)

Full text not currently available from Enlighten.


We treat the problem of movement prediction as a classification task. We assume the existence of a (gradually populated and/or trained) knowledge base and try to compare the movement pattern of a certain object with stored information in order to predict its future location. We introduce a novel distance metric function based on weighted spatial and velocity context used for location prediction. The proposed distance metric is compared with other distance metrics in the literature on real traffic data and reveals its superiority.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos
Authors: Anagnostopoulos, T., Anagnostopoulos, C., Hadjiefthymiades, S., and Zaslavsky, A.
Subjects:Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
College/School:College of Science and Engineering > School of Computing Science
Journal Name:International Journal of Wireless Information Networks
Publisher:Springer US
ISSN (Online):1572-8129

University Staff: Request a correction | Enlighten Editors: Update this record