Issues and Techniques of Spatio -Temporal Rule Mining for Location Based Services

Mr. M.Jayakameswaraiah; Dr. S.Ramakrishna

Issues and Techniques of Spatio -Temporal Rule Mining for Location Based Services

Mr. M.Jayakameswaraiah * §

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Dr. S.Ramakrishna

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SRI VENKATESWARA UNIVERSITY

Issues and Techniques of Spatio -Temporal Rule Mining for Location Based Services

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CST391R7

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Abstract

The Convergence of location-aware devices, wireless communication, such as the increasing accuracy of GPS technology and geographic information system functionalities enables the deployment of new services such as location-based services (LBS). Achieve high quality or such services, spatio-temporal data mining techniques are needed. Our work concentrates on the development of data mining techniques for knowledge discovery and delivery in LBS. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed.

References

6 Cites in Article

Reference Format

C. -Y Chow,M Mokbel,X Liu (2013). A Peer-to-Peer Spatial Cloaking Algorithm for Anonymous Issues and Techniques of Spatio -Temporal Rule Mining for Location Based Services.
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Haibo Hu,Dik-Lun Lee (2005). GAMMA: A Framework for Moving Object Simulation.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mr. M.Jayakameswaraiah, Dr. S.Ramakrishna. 2013. "Issues and Techniques of Spatio -Temporal Rule Mining for Location Based Services". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C7).

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GJCST Volume 13 Issue C7

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Data mining location based services spatial data spatio-temporal rule mining

Classification

GJCST-C Classification H.2.8

Submission ReceivedDecember 9, 2012
Peer Review Double Blind
Handling Editor
Accepted January 4, 2013
Published January 15, 2013

Version of record

v1.2

Issue date

July 2, 2013

Language

English

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Article Matrices

Total Score: 147

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Mr. M.Jayakameswaraiah, Dr. S.Ramakrishna (PhD/Dr. count: 1)

View Count (all-time): 386

Total Views (Real + Logic): 4074

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Publish Date: 2013 01, Tue

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Total Views: 4.1K

Total Downloads: 369

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