An Enhanced Approach for Compress Transaction Databases

v.vidhya rani

An Enhanced Approach for Compress Transaction Databases

Dr. vidhya rani * §

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§ Avinashilingam deemed university for women,coimabtore

An Enhanced Approach for Compress Transaction Databases

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Abstract

Associative rule mining is defined as the task that deals with the extraction of hidden knowledge and frequent patterns from very large databases. Traditional associative mining processes are iterative, time consuming and storage expensive. To solve these processes, a way of representation that reduces this size and at the same time maintains all the important and relevant data needed to extract the desired knowledge from transaction databases is needed. This paper proposes a method that merges the transactions in the transaction database and uses FP-Growth algorithm for mining associative knowledge is presented. The experimental results in terms of compression ratio, both in terms of storage required and number of transactions, prove that the proposed algorithm is an improved version to the existing systems.

References

5 Cites in Article

Reference Format

1. J Park,M Chen,P Yu (1995). An effective hash-based algorithm for mining association rules. Proceeding of the 1995 ACM-SIGMOD International Conference on Management of Data (SIGMOD'95), 175-186.
2. R Agrawal,J Shafer (1996). Parallel mining of association rules. IEEE Transactions on Knowledge and Data Engineering, 8(6), 962-969.
3. Aristides Gionis,Heikki Mannila,Taneli Mielikäinen,Panayiotis Tsaparas (2007). Assessing data mining results via swap randomization. ACM Transactions on Knowledge Discovery from Data, 1(3), 14.
4. J Dai,D Yang,J Wu,M Hung (2008). An Efficient Data Mining Approach on Compressed Transactions. International Journal of Electrical and Computer Engineering, 3(2), 76-83.
5. R Bayardo (1998). Efficiently mining long patterns from databases. Proceeding of the 1998 ACM

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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

v.vidhya rani. . "An Enhanced Approach for Compress Transaction Databases". Global Journal of Computer Science and Technology GJCST Volume 12 (GJCST Volume 12 Issue 2).

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GJCST Volume 12 Issue 2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Associative Rule Mining Compact Transactional Database FP-Growth FP-Tree Frequent Pattern Generation Merge Transactions

Classification

GJCST Classification H.2.8

H.2.4

Submission ReceivedApril 6, 2012
Peer Review Double Blind
Handling Editor
Accepted May 3, 2012
Published May 15, 2012

Version of record

v1.2

Issue date

February 6, 2012

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: I.Elizabeth shanthi,v.vidhya rani (PhD/Dr. count: 0)

View Count (all-time): 401

Total Views (Real + Logic): 6261

Total Downloads (simulated): 423

Publish Date: 2012 05, Tue

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Total Views: 6.3K

Total Downloads: 423

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