改进apriorissome算法在超市O2O营销中的应用

2019 3rd International Conference on Data Science and Business Analytics (ICDSBA) Pub Date : 2019-10-01 DOI:10.1109/ICDSBA48748.2019.00084

Yaxin Zhao, Shi Ning

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引用次数: 2

摘要

序列模式挖掘是数据分析的关键技术。利用Python语言及其IDE工具PyCharm可以有效地挖掘超市O2O营销产生的交易数据集。本文对已有的AprioriSome算法进行了改进，增加了时间间隔、时间窗等约束条件，并将其应用于河南某大型连锁超市的真实交易数据集。结果表明，改进的AprioriSome算法的运行时间缩短，挖掘的频繁序列数量明显增加，更加实用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of Improved AprioriSome Algorithm in Supermarket O2O Marketing

Sequential pattern mining is the key technology for analyzing data. Using Python language and its IDE tool PyCharm can effectively mine the transaction data set generated by supermarket O2O marketing. In this paper, the existing AprioriSome algorithm is improved, and the constraints such as time interval and time window are added, and it is applied to the real transaction data set of a large supermarket chain in Henan. The results show that the running time of the improved AprioriSome algorithm is reduced, and the number of frequent sequences excavated is obviously increased and more practical.

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2019 3rd International Conference on Data Science and Business Analytics (ICDSBA)

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