AN EFFICIENT SAMPLING APPROACH FOR MINING ALL ASSOCIATION RULES IN LARGE DATABASES

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DEYPIR M.; SADR ALDINI M.H.

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Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE) Year:2008 | Volume:7 | Issue:1 Page(s): 73-78

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Information Journal Paper

Title

AN EFFICIENT SAMPLING APPROACH FOR MINING ALL ASSOCIATION RULES IN LARGE DATABASES

Author(s)

DEYPIR M. | SADR ALDINI M.H. | Issue Writer Certificate

Keywords

DATA MINING

ASSOCIATIONS RULE MINING

APRIORI

SAMPLING

FP-GROWTH

Abstract

Mining association rules is an interesting problem in the field of knowledge discovery and DATA MINING. In this paper a fast, new method for mining association rules is presented. In this new SAMPLING approach, which utilizes FP-GROWTH to mine sample data, the candidate generation and test in the sample data is omitted because of the FP-Tree projection of sample data in the main memory. To overcome the main memory limitation in the new SAMPLING method, a useful technique is proposed. Theoretical time consideration and empirical evaluation show that the new SAMPLING approach is superior to the traditional APRIORI-based SAMPLING by orders of magnitude. Experimental evaluations on artificial and real-life datasets show that our approach, compared with a previously proposed SAMPLING algorithm, is more efficient when the minimal support threshold is decreased and is also more stable as the size of the sample data increases.

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APA: Copy

DEYPIR, M., & SADR ALDINI, M.H.. (2008). AN EFFICIENT SAMPLING APPROACH FOR MINING ALL ASSOCIATION RULES IN LARGE DATABASES. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), 7(1), 73-78. SID. https://sid.ir/paper/283430/en

Vancouver: Copy

DEYPIR M., SADR ALDINI M.H.. AN EFFICIENT SAMPLING APPROACH FOR MINING ALL ASSOCIATION RULES IN LARGE DATABASES. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE)[Internet]. 2008;7(1):73-78. Available from: https://sid.ir/paper/283430/en

IEEE: Copy

M. DEYPIR, and M.H. SADR ALDINI, “AN EFFICIENT SAMPLING APPROACH FOR MINING ALL ASSOCIATION RULES IN LARGE DATABASES,” IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), vol. 7, no. 1, pp. 73–78, 2008, [Online]. Available: https://sid.ir/paper/283430/en

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