On-line discovery of hot motion paths

Sacharidis, D; Patroumpas, K; Terrovitis, M; Kantere, V; Potamias, M; Mouratidis, K; Sellis, T

dc.contributor.author	Sacharidis, D	en
dc.contributor.author	Patroumpas, K	en
dc.contributor.author	Terrovitis, M	en
dc.contributor.author	Kantere, V	en
dc.contributor.author	Potamias, M	en
dc.contributor.author	Mouratidis, K	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T02:45:42Z
dc.date.available	2014-03-01T02:45:42Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32336
dc.subject	Moving Object	en
dc.subject	Multiple Objectives	en
dc.subject	Resource Allocation	en
dc.subject	Synthetic Data	en
dc.subject.other	Approximation theory	en
dc.subject.other	Data structures	en
dc.subject.other	Problem solving	en
dc.subject.other	Search engines	en
dc.subject.other	Uncertainty analysis	en
dc.subject.other	Location sensing devices	en
dc.subject.other	Positional measurements	en
dc.subject.other	Online searching	en
dc.title	On-line discovery of hot motion paths	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1353343.1353392	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1353343.1353392	en
heal.publicationDate	2008	en
heal.abstract	We consider an environment of numerous moving objects, equipped with location-sensing devices and capable of communicating with a central coordinator. In this setting, we investigate the problem of maintaining hot motion paths, i.e., routes frequently followed by multiple objects over the recent past. Motion paths approximate portions of objects' movement within a tolerance margin that depends on the uncertainty inherent in positional measurements. Discovery of hot motion paths is important to applications requiring classification/profiling based on monitored movement patterns, such as targeted advertising, resource allocation, etc. To achieve this goal, we delegate part of the path extraction process to objects, by assigning to them adaptive lightweight filters that dynamically suppress unnecessary location updates and, thus, help reducing the communication overhead. We demonstrate the benefits of our methods and their efficiency through extensive experiments on synthetic data sets. Copyright 2008 ACM.	en
heal.journalName	Advances in Database Technology - EDBT 2008 - 11th International Conference on Extending Database Technology, Proceedings	en
dc.identifier.doi	10.1145/1353343.1353392	en
dc.identifier.spage	392	en
dc.identifier.epage	403	en