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Research on methods of improving customer profile in electric power marketing based on big data analysis of customer's electricity address

机译:基于客户用电地址大数据分析的电力营销中提高客户形象的方法研究

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The paper is aimed at solving the problems of inconsistency, inaccuracy and non-real time of customer profile in the electric power marketing information system, and proposes the new methods of improving the customer profile in electric power marketing based on the big data analysis of customer's addresses. The core idea of the methods is that by the introduction of other industry data resources, the electricity address provided by electric power marketing information system and the customer address provided by other resources are analyzed with the big data technologies to achieve precise matching of these addresses. The address matching is followed by three steps: Chinese word segmentation with Hidden Markov Model algorithm, sentence similarity calculation based on the semantic and word order, and finally geographical coordinates matching for cross validation. Based on the matching results, the procedures of updating customer profile are processed respectively according to customer contact changes or changes in customer property rights, to achieve the consistency, accuracy and real-time data of customer profile. By implementing the automatic and intelligent operations of perfecting customer profile, the strong information support is provided for the marketing departments to enhance the “Internet+” electric power marketing services.
机译:本文旨在解决电力营销信息系统中客户档案的不一致,不准确和不实时的问题,并基于客户的大数据分析,提出了改善电力营销中客户档案的新方法。地址。该方法的核心思想是通过引入其他行业数据资源,利用大数据技术对电力销售信息系统提供的用电地址和其他资源提供的客户地址进行分析,以实现这些地址的精确匹配。地址匹配分为三个步骤:使用隐马尔可夫模型算法进行中文分词,基于语义和单词顺序的句子相似度计算以及最终的地理坐标匹配以进行交叉验证。根据匹配结果,根据客户联系方式的变化或客户产权的变化,分别处理客户资料的更新过程,以达到客户资料的一致性,准确性和实时性。通过实施完善客户档案的自动和智能操作,为营销部门提供了强大的信息支持,以增强“ Internet +”电力营销服务。

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