Querying continuous recurrent convoys of interest

Publication Type

Conference Proceeding Article

Publication Date

11-2019

Abstract

Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on a real-life trajectory database show the efficiency of our method.

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2019

First Page

436

Last Page

439

ISBN

9781450369091

Identifier

10.1145/3347146.3359083

City or Country

Chicago, IL, USA

Additional URL

http://doi.org/10.1145/3347146.3359083

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