首页> 外文会议>Advances in Knowledge Discovery and Data Mining >Mining Relationship Graphs for Effective Business Objectives
【24h】

Mining Relationship Graphs for Effective Business Objectives

机译:挖掘关系图以实现有效的业务目标

获取原文

摘要

Modern organization has two types of customer profiles: active and passive. Active customers contribute to the business goals of an organization, while passive customers are potential candidates that can be converted to active ones. Existing KDD techniques focused mainly on past data generated by active customers. The insights discovered apply well to active ones but may scale poorly with passive customers. This is because there is no attempt to generate know-how to convert passive customers into active ones. We propose an algorithm to discover relationship graphs using both types of profile. Using relationship graphs, an organization can be more effective in realizing its goals.
机译:现代组织有两种类型的客户档案:主动和被动。主动客户有助于组织的业务目标,而被动客户是可以转换为主动客户的潜在候选人。现有的KDD技术主要集中在活跃客户生成的过去数据上。发现的洞察力很好地适用于主动的洞察力,但对于被动的客户可能无法很好地扩展。这是因为没有尝试产生专有技术来将被动客户转换为主动客户的尝试。我们提出了一种使用两种类型的配置文件发现关系图的算法。使用关系图,组织可以更有效地实现其目标。

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