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Domain knowledge based segmentation of online banking customers

机译:基于领域知识的在线银行客户细分

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摘要

The share of the services offered via the Internet by nowadays banking companies is quickly growing, making of the understanding of online customers one of the major concerns. Data mining tools have proven their efficiency in addressing this challenge by providing unsupervised quantitative techniques to identify those segments of customers with similar characteristics. This paper will focus on segmenting an online banking customer base in a meaningful way for the business by enhancing an unsupervised quantitative technique approach with domain knowledge. Both traditional and knowledge-based approaches will be applied and evaluated. Thanks to an extensive description and discussion of the new insights, the complementarity of the two approaches is illustrated.
机译:如今,银行公司通过Internet提供的服务所占的份额正在迅速增长,这使得对在线客户的了解成为主要问题之一。数据挖掘工具通过提供无监督的定量技术来识别具有相似特征的那些客户群体,证明了其应对这一挑战的效率。本文将着重于通过增强具有领域知识的无监督量化技术方法,以一种有意义的方式对网络银行客户群进行业务细分。传统方法和基于知识的方法都将被应用和评估。由于对新见解进行了广泛的描述和讨论,因此说明了这两种方法的互补性。

著录项

  • 来源
    《Intelligent data analysis 》 |2015年第suppla期| S163-S184| 共22页
  • 作者单位

    Univ Los Andes, Fac Engn & Appl Sci, Santiago, Chile|Katholieke Univ Leuven, Dept Decis Sci & Informat Management, Leuven, Belgium;

    Katholieke Univ Leuven, Dept Decis Sci & Informat Management, Leuven, Belgium;

    Katholieke Univ Leuven, Dept Decis Sci & Informat Management, Leuven, Belgium|Univ Southampton, Sch Management, Highfield Southampton, England|Vlerick, Leuven Gent Management Sch, Ghent, Belgium;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Data mining; constrained clustering; customer profiling; domain knowledge; direct marketing; banking;

    机译:数据挖掘;约束聚类;客户分析;领域知识;直接营销;银行业务;

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