Research on improved algorithm of FP-growth based on data strong association

Qianhao Ye; Shiyong Ning

doi:10.1117/12.3011478

7 December 2023 Research on improved algorithm of FP-growth based on data strong association

Qianhao Ye, Shiyong Ning

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294115 (2023) https://doi.org/10.1117/12.3011478
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

FP-Growth algorithm is a classic algorithm in the field of data mining. Compared with Apriori algorithm, all frequent item sets can be obtained by traversing the data set only twice, which improves the efficiency of data mining. However, in practical use, if there are many Frequent one item sets in the data set, the data set is scattered, and a lot of time will be wasted. Moreover, it will cause the problem that there are too many child nodes when FP-Tree is formed, and it is easy to overflow. In view of the above shortcomings, in this paper, a new FP-Growth algorithm based on Data Strong Association (SDA-FP-Growth algorithm) is proposed., which uses frequent two items set for operation integration and merging of the same leaf nodes, which is conducive to the subsequent frequent item set search. Experiments show that the SDA-FPGrowth algorithm reduces the running time and memory space.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qianhao Ye and Shiyong Ning "Research on improved algorithm of FP-growth based on data strong association", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294115 (7 December 2023); https://doi.org/10.1117/12.3011478

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