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Using Hybrid Data Mining Techniques for Facilitating Cross-selling of a Mobile Telecom Market to develop Customer Classification Model

机译:使用混合数据挖掘技术来促进移动电信市场的跨销售开发客户分类模型

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As the competition between mobile telecom operators becomes severe, it becomes critical for operators to diversify their business areas. Especially, the mobile operators are turning from traditional voice communication to mobile value-added services (VAS), which are new services to generate more ARPU (average revenue per user). That is, cross-selling is critical for mobile telecom operators to expand their revenues and profits. In this study, we propose a customer classification model. Our model uses the cumulated data on the existing customers including the patterns for using old products or services to find prospects for purchasing. The data mining techniques are applied to our proposed model in two steps. In the first step, several classification techniques are applied independently. In the second step, our model compromises all these probabilities by using genetic algorithm. To validate the usefulness of our model, we applied it to a real-world mobile telecom company's case in Korea.
机译:随着移动电信运营商之间的竞争变得严重,运营商对其业务区多元化的竞争。特别是,移动运营商正在从传统的语音通信转向移动增值服务(VAS),这是生成更多ARPU的新服务(每个用户的平均收入)。也就是说,跨销售对于移动电信运营商来说至关重要,扩大他们的收入和利润。在这项研究中,我们提出了客户分类模型。我们的模型使用现有客户的累积数据,包括使用旧产品或服务的模式,以寻找购买前景。数据挖掘技术以两个步骤应用于我们所提出的模型。在第一步中,独立地应用了几种分类技术。在第二步中,我们的模型通过使用遗传算法来损害所有这些概率。为了验证我们模型的有用性,我们将其应用于韩国真实的移动电信公司的案例。

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