Abstract
ABSTRACT Measuring similarity of GPS trajectories has attracted a lot of attention in recent years. As a result, multiple trajectory similarity measures have been developed and are used in a wide set of applications which aim to extract meaningful information from large collections. In this paper, we focus on some of the most popular measures and study how they all can be adapted to use contextual information. We experiment using the buildings in an urban setting as the context and demonstrate how it impacts the similarity values. Experiments show that routes rank differently in terms of similarity in the presence of context which can have serious implications in applications such as trajectory search and clustering similar trajectories.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
