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Association Rule Mining for Precision Marketing of Power Companies with User Features Extraction

机译：协会规则挖掘电力公司的精确营销与用户特征提取

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摘要

To help power companies quickly and precisely find target consumers for different purposes from resident users, a method based on association rule mining is proposed. First, users’ four electricity features including daily electricity consumption (DEC), electricity consumption stability (ECS), potential of peak load shifting (PPLS) and typical electricity consumption patterns (TECP) and basic attributes (population, employment status, cooking type, etc.) are extracted. Then, the association rules between basic attributes and electricity features are obtained by FP-growth algorithm, which can guide power companies to select the target users. Finally, using a sample to evaluate obtained rules, the results demonstrate that the proposed method is practical and effective.
机译：为了帮助电力公司快速，精确地查找目标消费者以获取不同目的的目的，提出了一种基于关联规则挖掘的方法。首先，用户的四种电力特征包括每日电力消耗（DEC），电力消耗稳定性（ECS），峰值负荷转移（PPLS）和典型电力消耗模式（TECP）和基本属性（人口，就业状态，烹饪类型，等）被提取。然后，基本属性和电力功能之间的关联规则是由FP-Grows算法获得的，可以指导电力公司选择目标用户。最后，使用样品来评估获得的规则，结果表明该方法是实用且有效的。

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