首页> 外文期刊>Fuzzy sets and systems >A methodology for dynamic data mining based on fuzzy clustering
【24h】

A methodology for dynamic data mining based on fuzzy clustering

机译:基于模糊聚类的动态数据挖掘方法

获取原文
获取原文并翻译 | 示例

摘要

Dynamic data mining is increasingly attracting attention from the respective research community. On the other hand, users of installed data mining systems are also interested in the related techniques and will be even more since most of these installations will need to be updated in the future. For each data mining technique used, we need different methodologies for dynamic data mining. In this paper, we present a methodology for dynamic data mining based on fuzzy clustering. Using the implementation of the proposed system we show its benefits in two application areas; customer segmentation and traffic management.
机译:动态数据挖掘越来越引起各个研究领域的关注。另一方面,已安装的数据挖掘系统的用户也对相关技术感兴趣,并且由于将来需要更新其中的大多数安装,因此将更加感兴趣。对于所使用的每种数据挖掘技术,我们需要不同的方法来进行动态数据挖掘。在本文中,我们提出了一种基于模糊聚类的动态数据挖掘方法。通过使用提议的系统的实现,我们在两个应用领域中展示了它的优势;客户细分和流量管理。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号