A New Classification Method to Overcome Over—Branching

Classification is an important technique in data mining.The decision trees builty by most of the existing classification algorithms commonly feature over-branching,which will lead to poor efficiency in the subsequent classification period.In this paper,we present a new value-oriented classification method,which aims at building accurately proper-sized decision trees while reducing over-branching as much as possible,based on the concepts of frequent-pattern-node and exceptive-child-node.The experiments show that while using relevant anal-ysis as pre-processing ,our classification method,without loss of accuracy,can eliminate the over-branching greatly in decision trees more effectively and efficiently than other algorithms do.     

一个面向大规模数据库的数据挖掘系统

数据挖掘融合了数据库技术、人工智能和统计学,是目前的研究热点.为了能够集成当前数据挖掘的主要技术并使它们协同工作,在进行数据挖掘基本算法研究的基础上研制开发了一个数据挖掘系统--Golden-Eye.系统实现了在数据挖掘研究中的一些最新成果,集成了泛化、数据清洗这两个数据准备操作以及关联规则发现、例外规则发现、时序模式发现、分类器构造、聚类分析等基本数据挖掘操作,并实现了对挖掘操作的基本管理和结果的图形化显示.整个框架设计充分体现了系统的完整性、协调性和高效性:自底向上将存储控制模块、数据预处理模块、挖掘操作模块、挖掘库管理模块有机地结合在一起,在底层实现了对包括中间结果在内的数据的统一管理,在上层为用户提供了可视化的界面.实验结果表明,该系统能够在大规模数据库上成功地完成用户所指定的数据挖掘操作.     

Clustering DTDs: An Interactive Two-Level Approach

XML（eXtensible Markup Language)is a standard which is widely applied in data representation and data exchange,However,as an important concept of XML,DTD(Document Type Definition)is not taken full advantage in current applications.In this paper,a new method for clustering DTDs is presented.and it can be used in XML document clustering.The two-level method clusters the elements in DTDs and clusters DTDs separately.Element clustering forms the first level and provides element clusters,which are the generalization of relevant elements.DTD clustering utilizes the generalized information and forms the second level in the whole clustering process.The two-level method has the following advantages:1) It takes into consideration both the content and the structure within DTDs;2) The generalized information about elements is more useful than the separated words in the vector model;3) The two-level method facilitates the searching of outliers.The experiments show that this method is able to categorize the relevant DTDs effectively.