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An Exploratory Approach for Understanding Customer Behavior Processes Based on Clustering and Sequence Mining

机译:基于聚类和序列挖掘的客户行为过程理解的探索方法

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In this paper, a novel approach towards enabling the exploratory understanding of the dynamics inherent in the capture of customers' data at different points in time is outlined. The proposed methodology combines state-of-art data mining clustering techniques with a tuned sequence mining method to discover prominent customer behavior trajectories in data bases, which - when combined - represent the "behavior process" as it is followed by particular groups of customers. The framework is applied to a real-life case of an event organizer; it is shown how behavior trajectories can help to explain consumer decisions and to improve business processes that are influenced by customer actions.
机译:在本文中,概述了一种新的方法,探讨了对不同点在不同点处捕获客户数据捕获中固有的动态的探索性的方法。所提出的方法将最先进的数据挖掘聚类技术与调谐序列挖掘方法结合起来,以发现数据库中的突出客户行为轨迹,这 - 组合 - 代表“行为过程”,因为它之后是特定的客户组。该框架应用于事件组织者的真实情况;显示行为轨迹如何有助于解释消费者决策,并改善受客户行动影响的业务流程。

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