An Improved Apriori Algorithm based on Matrix Data Structure

Shalini Dutt; Naveen Choudhary

An Improved Apriori Algorithm based on Matrix Data Structure

Shalini Dutt * §

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Naveen Choudhary ‡

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§ College of Technology and Engineering, Maharana Prat...

‡ Maharana Pratap University of Agriculture and Techno...

An Improved Apriori Algorithm based on Matrix Data Structure

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Abstract

Mining regular/frequent itemsets is very important concept in association rule mining which shows association among the variables in huge database. the classical algorithm used for extracting regular itemsets faces two fatal deficiencies .firstly it scans the database multiple times and secondly it generates large number of irregular itemsets hence increases spatial and temporal complexties and overall decreases the efficiency of classical apriori algorithm.to overcome the limitations of classical algorithm we proposed an improved algorithm in this paper with a aim of minimizing the temporal and spatial complexities by cutting off the database scans to one by generating compressed data structure bit matrix(b_matrix)-and by reducing redundant computations for extracting regular itemsets using top down method. theoritical analysis and experimental results shows that improved algorithm is better than classical apriori algorithm.

References

10 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

Shalini Dutt, Naveen Choudhary. 2014. "An Improved Apriori Algorithm based on Matrix Data Structure". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C5).

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GJCST Volume 14 Issue C5

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Apriori Algorithm Association rule frequent itemsets

Classification

E.1

Submission ReceivedDecember 11, 2013
Peer Review Double Blind
Handling Editor
Accepted January 3, 2014
Published July 28, 2014

Version of record

v1.2

Issue date

July 28, 2014

Language

English

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Article Matrices

Total Score: 103

Country: India

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Shalini Dutt, Naveen Choudhary, Dharm Singh (PhD/Dr. count: 0)

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