Title
A hybrid model and computing platform for spatio-semantic trajectories
Abstract
Spatio-temporal data management has progressed significantly towards efficient storage and indexing of mobility data. Typically such mobility data analytics is assumed to follow the model of a stream of (x,y,t) points, usually coming from GPS-enabled mobile devices. With large-scale adoption of GPS-driven systems in several application sectors (shipment tracking to geo-social networks), there is a growing demand from applications to understand the spatio-semantic behavior of mobile entities. Spatio-semantic behavior essentially means a semantic (and preferably contextual) abstraction of raw spatio-temporal location feeds. The core contribution of this paper lies in presenting a Hybrid Model and a Computing Platform for developing a semantic overlay - analyzing and transforming raw mobility data (GPS) to meaningful semantic abstractions, starting from raw feeds to semantic trajectories. Secondly, we analyze large-scale GPS data using our computing platform and present results of extracted spatio-semantic trajectories. This impacts a large class of mobile applications requiring such semantic abstractions over streaming location feeds in real systems today.
Year
DOI
Venue
2010
10.1007/978-3-642-13486-9_5
ESWC (1)
Keywords
Field
DocType
spatio-semantic trajectory,raw mobility data,hybrid model,semantic overlay,computing platform,semantic abstraction,mobility data,spatio-temporal data management,large-scale gps data,mobility data analytics,meaningful semantic abstraction,spatio-semantic behavior,mobile device,social network
Data mining,Abstraction,Data analysis,Computer science,Search engine indexing,Mobile device,Global Positioning System,Overlay,Data management,Semantic computing,Database
Conference
Volume
ISSN
ISBN
6088
0302-9743
3-642-13485-8
Citations 
PageRank 
References 
45
1.91
12
Authors
4
Name
Order
Citations
PageRank
Zhixian Yan172634.14
Christine Parent21391203.77
Stefano Spaccapietra32603565.28
Dipanjan Chakraborty41761118.69