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)

Abstract

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
• Status: Published
• Refereed: Yes
• 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: 1068-9605
• ISSN (Online): 1572-8129