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首页> 外文期刊>電子情報通信学会技術研究報告. 人工知能と知識処理. Artificial Intelligence and Knowledge Based Processing >Knowledge Discovery from Consumer Behavior in an Alcohol Market by Using Graph Mining Technique - An Example of Using an Active Mining Process for a Typical Business Application
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Knowledge Discovery from Consumer Behavior in an Alcohol Market by Using Graph Mining Technique - An Example of Using an Active Mining Process for a Typical Business Application

机译:通过使用图挖掘技术从酒精市场中的消费者行为中发现知识-对于典型的业务应用程序使用主动挖掘过程的示例

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This paper deals with an actual case of the business application of graph mining techniques to purchase history data that employs an active mining process and the verification of the practical utility of the final results. While the current data mining process emphasizes iterative analysis of a given data, active mining is based on user interest levels and both the data and the process evolve dynamically in the form of a spiral configuration. In this paper, we describe the process of how new knowledge concerning consumer behavior in the alcoholic beverage market was discovered and how, based on this, new sales promotion planning was carried out and the effects were verified.
机译:本文讨论了图形挖掘技术在商业应用中购买历史数据的实际案例,该案例采用了活跃的挖掘过程并验证了最终结果的实用性。当前的数据挖掘过程强调对给定数据的迭代分析,而主动挖掘则基于用户兴趣级别,并且数据和过程都以螺旋配置的形式动态发展。在本文中,我们描述了如何发现有关酒精饮料市场中消费者行为的新知识的过程,以及在此基础上如何执行新的促销计划并验证其效果的过程。

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