Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases

Florian Verhein, Sanjay Chawla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

53 Citations (Scopus)

Abstract

As mobile devices proliferate and networks become more locationaware, the corresponding growth in spatio-temporal data will demand analysis techniques to mine patterns that take into account the semantics of such data. Association Rule Mining has been one of the more extensively studied data mining techniques, but it considers discrete transactional data (supermarket or sequential). Most attempts to apply this technique to spatial-temporal domains maps the data to transactions, thus losing the spatio-temporal characteristics. We provide a comprehensive definition of spatio-temporal association rules (STARs) that describe how objects move between regions over time. We define support in the spatio-temporal domain to effectively deal with the semantics of such data. We also introduce other patterns that are useful for mobility data; stationary regions and high traffic regions. The latter consists of sources, sinks and thorough-fares. These patterns describe important temporal characteristics of regions and we show that they can be considered as special STARs. We provide efficient algorithms to find these patterns by exploiting several pruning properties1.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages187-201
Number of pages15
Volume3882 LNCS
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event11th International Conference on Database Systems for Advanced Applications, DASFAA 2006 - Singapore, Singapore
Duration: 12 Apr 200615 Apr 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3882 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other11th International Conference on Database Systems for Advanced Applications, DASFAA 2006
CountrySingapore
CitySingapore
Period12/4/0615/4/06

Fingerprint

Association rules
Association Rules
Mining
Databases
Semantics
Mobile devices
Data mining
Wireless networks
Spatio-temporal Data
Association Rule Mining
Mobile Networks
Pruning
Mobile Devices
Transactions
Data Mining
Efficient Algorithms
Temporal Lobe
Object
Traffic
Equipment and Supplies

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Verhein, F., & Chawla, S. (2006). Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3882 LNCS, pp. 187-201). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3882 LNCS). https://doi.org/10.1007/11733836_15

Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases. / Verhein, Florian; Chawla, Sanjay.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3882 LNCS 2006. p. 187-201 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3882 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Verhein, F & Chawla, S 2006, Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3882 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3882 LNCS, pp. 187-201, 11th International Conference on Database Systems for Advanced Applications, DASFAA 2006, Singapore, Singapore, 12/4/06. https://doi.org/10.1007/11733836_15
Verhein F, Chawla S. Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3882 LNCS. 2006. p. 187-201. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11733836_15
Verhein, Florian ; Chawla, Sanjay. / Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3882 LNCS 2006. pp. 187-201 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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