Spatial keyword range search on trajectories

Han, Y; Wang, L; Zhang, Y; Zhang, W; Lin, X

Spatial keyword range search on trajectories

Han, Y Wang, L Zhang, Y

Zhang, W Lin, X

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 9050 pp. 223 - 240
Issue Date:: 2015-01-01

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Field	Value	Language
dc.contributor.author	Han, Y	en_US
dc.contributor.author	Wang, L	en_US
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638	en_US
dc.contributor.author	Zhang, W	en_US
dc.contributor.author	Lin, X	en_US
dc.date.issued	2015-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, 9050 pp. 223 - 240	en_US
dc.identifier.isbn	9783319181226	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41651
dc.description.abstract	© 2015, Springer International Publishing Switzerland, All rights Reserved. With advances in geo-positioning technologies and ensuing location based service, there are a rapid growing amount of trajectories associated with textual information collected in many emerging applications. For instance, nowadays many people are used to sharing interesting experience through Foursquare or Twitter along their travel routes. In this paper, we investigate the problem of spatial keyword range search on trajectories, which is essential to make sense of large amount of trajectory data. To the best of our knowledge, this is the first work to systematically investigate range search over trajectories where three important aspects, i.e., spatio, temporal and textual, are all taken into consideration. Given a query region, a timespan and a set of keywords, we aim to retrieve trajectories that go through this region during query timespan, and contain all the query keywords. To facilitate the range search, a novel index structure called IOC-Tree is proposed based on the inverted indexing and octree techniques to effectively explore the spatio, temporal and textual pruning techniques. Furthermore, this structure can also support the query with order-sensitive keywords. Comprehensive experiments on several real-life datasets are conducted to demonstrate the efficiency.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-18123-3_14	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Spatial keyword range search on trajectories	en_US
dc.type	Conference Proceeding
utslib.citation.volume	9050	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	9050	en_US

Abstract:

© 2015, Springer International Publishing Switzerland, All rights Reserved. With advances in geo-positioning technologies and ensuing location based service, there are a rapid growing amount of trajectories associated with textual information collected in many emerging applications. For instance, nowadays many people are used to sharing interesting experience through Foursquare or Twitter along their travel routes. In this paper, we investigate the problem of spatial keyword range search on trajectories, which is essential to make sense of large amount of trajectory data. To the best of our knowledge, this is the first work to systematically investigate range search over trajectories where three important aspects, i.e., spatio, temporal and textual, are all taken into consideration. Given a query region, a timespan and a set of keywords, we aim to retrieve trajectories that go through this region during query timespan, and contain all the query keywords. To facilitate the range search, a novel index structure called IOC-Tree is proposed based on the inverted indexing and octree techniques to effectively explore the spatio, temporal and textual pruning techniques. Furthermore, this structure can also support the query with order-sensitive keywords. Comprehensive experiments on several real-life datasets are conducted to demonstrate the efficiency.

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http://hdl.handle.net/10453/41651