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Application of Improved AprioriSome Algorithm in Supermarket O2O Marketing

机译:改进的试验算法在超市O2O营销中的应用

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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.
机译:顺序模式挖掘是用于分析数据的关键技术。使用Python语言及其IDE工具Pycharm可以有效地挖掘超市O2O营销生成的交易数据集。在本文中,提高了现有的试验组算法,并添加了诸如时间间隔和时间窗口的约束,并且应用于河南大型超市链的真实交易数据集。结果表明,改进的试验组算法的运行时间降低,挖掘出频繁序列的数量明显增加,更实用。

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