基于稀有项集挖掘的模式检测
Pattern Detection with Rare Item-set Mining
摘要：
随着可用数据量的爆炸式增长，在大型数据集中发现新的和有趣的模式，称为数据采掘，引起了越来越多的兴趣。数据采掘技术可以应用于不同的领域和领域，如计算机科学，卫生部门，保险，国土安全，银行和金融等，在本文中，我们感兴趣的发现一个特定类别的模式，被称为罕见的和不存在的模式。我们提出了一种新的方法对非本模式的发现使用稀有项集挖掘。
英文摘要：
The discovery of new and interesting patterns in large datasets, known as data mining, draws more and more interest as the quantities of available data are exploding. Data mining techniques may be applied to different domains and fields such as computer science, health sector, insurances, homeland security, banking and finance, etc. In this paper we are interested by the discovery of a specific category of patterns, known as rare and non-present patterns. We present a novel approach towards the discovery of non-present patterns using rare item-set mining.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
