Journal
2017 IEEE 14TH INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING (ICEBE 2017)
Volume -, Issue -, Pages 97-102Publisher
IEEE
DOI: 10.1109/ICEBE.2017.24
Keywords
frequent itemset mining; FP-growth; GPU; parallel computing
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Funding
- Collaborative Innovation Center of Wireless Communications Technology
- National Natural Science Foundation of China [61672152]
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This paper proposes and implements a parallel scheme of FP-growth algorithm and implements this parallel algorithm (PFP-growth algorithm). Experimental results show that, compared with FP-growth algorithm, PFP-growth algorithm is more efficient, and the larger the data set is, the lower the support threshold is, the more remarkable the speedup is.
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