DISCOVERING PATTERNS FROM TEMPORAL DATABASES USING TEMPORAL ASSOCIATION RULE

Dr.N. Ughazendi; Mr.N.Pughazendi

DISCOVERING PATTERNS FROM TEMPORAL DATABASES USING TEMPORAL ASSOCIATION RULE

Dr.N. Ughazendi * § M.E, Ph.D.,

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Mr.N.Pughazendi

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§ Anna University

DISCOVERING PATTERNS FROM TEMPORAL DATABASES USING TEMPORAL ASSOCIATION RULE

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Abstract

Data mining is the process of discovering and examining data from diverse viewpoint, using automatic or semiautomatic techniques to remove knowledge or useful information and discover correlations or meaningful patterns and rules from large databases. One of the most vital characteristic missed by the traditional data mining systems is their capability to record and process time-varying aspects of the real world databases. . Temporal data mining, which mines or discovers knowledge and patterns from temporal databases, is an extension of data mining with capability to include time attribute analysis. The pattern discovery task of temporal data mining discovers all patterns of interest from a large dataset. This paper presents an overview of temporal data mining and focus on pattern discovery using temporal association rules.

References

20 Cites in Article

Reference Format

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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

Dr.N. Ughazendi, Mr.N.Pughazendi. 1970. "DISCOVERING PATTERNS FROM TEMPORAL DATABASES USING TEMPORAL ASSOCIATION RULE". Global Journal of Computer Science and Technology GJCST Volume 11 (GJCST Volume 11 Issue 14).

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GJCST Volume 11 Issue 14

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Association Rules Pattern Discovery Temporal Data Mining Temporal Rules

Classification

GJCST Classification H.2.8

Submission ReceivedJune 21, 2011
Peer Review Double Blind
Handling Editor
Accepted July 18, 2011
Published July 29, 2011

Version of record

v1.2

Issue date

August 2, 2011

Language

English

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Article Matrices

Total Score: 147

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Dr.N. Ughazendi, Mr.N.Pughazendi (PhD/Dr. count: 1)

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Publish Date: 2011 07, Fri

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