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A fast algorithm for mining association rules

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Abstract

In this paper, the problem of discovering association rules between items in a lange database of sales transactions is discussed, and a novel algorithm, BitMatrix, is proposed. The proposed algorithm is fundamentally different from the known algorithms Apriori and AprioriTid. Empirical evaluation shows that the algorithm outperforms the known ones for large databases. Scale-up experiments show that the algorithm scales linearly with the number of transactions.

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References

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Correspondence to Huang Liusheng.

Additional information

This work was supported in part by the National ‘863’ High-Tech Programme of China (No. 863-306-ZD06-2).

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Huang, L., Chen, H., Wang, X. et al. A fast algorithm for mining association rules. J. Comput. Sci. & Technol. 15, 619–624 (2000). https://doi.org/10.1007/BF02948845

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  • DOI: https://doi.org/10.1007/BF02948845

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