检索结果-内蒙古大学图书馆

A Depth-first Algorithm of Finding All Association Rules Generated by a Frequent Itemset

Journal of Donghua University(English Edition) 2006年第6期23卷 1-4,9页

作者：武坤姜保庆魏庆 Institute of Data and Knowledge Engineering Henan University Institute of Data and Knowledge Engineering Henan University The Computer Science Department Henan University of Finance and Economics

The classical algorithm of finding association rules generated by a frequent itemset has to generate all non-empty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient.

关键词： association rule frequent itemset breath-first,depth-first consequent.

来源：评论

学校读者我要写书评

暂无评论

Mining Maximal Frequent Patterns in a Unidirectional FP-tree

引用

Journal of Donghua University(English Edition) 2006年第6期23卷 105-109页

作者：宋晶晶刘瑞新王艳姜保庆 Institute of Data and Knowledge Engineering Henan University Information Engineering Science Department Yellow River Conservancy Technical Institute

Because mining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model only finds out the maximal frequent patterns, which can generate all frequent patterns. FP-growth algorithm is one of the most efficient frequent-pattern mining methods published so far. However, because FP-tree and conditional FP-trees must be two-way traversable, a great deal memory is needed in process of mining. This paper proposes an efficient algorithm Unid_FP-Max for mining maximal frequent patterns based on unidirectional FP-tree. Because of generation method of unidirectional FP-tree and conditional unidirectional FP-trees, the algorithm reduces the space consumption to the fullest extent. With the development of two techniques: single path pruning and header table pruning which can cut down many conditional unidirectional FP-trees generated recursively in mining process, Unid_FP-Max further lowers the expense of time and space.

关键词： data mining frequent pattern the maximal frequent pattern Unid _ FP-tree conditional Unid _ FP-tree.

来源：评论

学校读者我要写书评

暂无评论

Depth-first algorithm of finding all association rules generated by a frequent itemset

引用

Journal of Donghua University (English Edition) 2006年第6期23卷 1-4+9页

作者： Wu, Kun Jiang, Bao-Qing Wei, Qing Institute of Data and Knowledge Engineering Henan University Kaifeng 475001 China Personnel Department Zhengzhou Institute of Aeronautical Industry Management Zhengzhou 450000 China Computer Science Department Henan University of Finance and Economics Zhengzhou 450000 China

The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient.

关键词： Association rules

来源：评论

学校读者我要写书评

暂无评论

TRIAS--An Algorithm for Mining Iceberg Tri-Lattices

TRIAS--An Algorithm for Mining Iceberg Tri-Lattices

引用

IEEE International Conference on data Mining (ICDM)

作者： Robert Jaschke Andreas Hotho Christoph Schmitz Bernhard Ganter Gerd Stumme Knowledge & Data Engineering Group University of Kassel Germany Institute for Algebra Dresden University of Technology Germany

In this paper, we present the foundations for mining frequent tri-concepts, which extend the notion of closed item-sets to three-dimensional data to allow for mining folk-sonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution as well as experimental results on a large real-world example.

关键词： data mining Itemsets Resource management Algorithm design and analysis Association rules data structures data engineering Algebra Lattices Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Mining Maximal Frequent Patterns in a Unidirectional FP-tree

引用

Journal of Donghua University(English Edition) 2006年第6期000卷 105-109页

作者： SONG Jing-jing LIU Rui-xin WANG Yan JIANG Bao-qing SONG Jing-jing(Institute of Data and Knowledge Engineering Henan University Kaifeng 475001) LIU Rui-xin(Information Engineering Science Department Yellow River Conservancy Technical Institute Kaifeng 475003) WANG Yan(Institute of Data and Knowledge Engineering Henan University Kaifeng 475001 Department of Computer Science and Application Zhengzhou Institute of Aeronautical Industry Management Zhengzhou 450015)

Becausemining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model only finds out the maximal frequent patterns, which can generate all frequent patterns. FP-growth algorithm is one of the most efficient frequent-pattern mining methods published so far. However,because FP-tree and conditional FP-trees must be two-way traversable, a great deal memory is needed in process of mining. This paper proposes an efficient algorithm Unid_FP-Max for mining maximal frequent patterns based on unidirectional FP-tree. Because of generation method of unidirectional FP-tree and conditional unidirectional FP-trees, the algorithm reduces the space consumption to the fullest extent. With the development of two techniques:single path pruning and header table pruning which can cut down many conditional unidirectional FP-trees generated recursively in mining process, Unid_ FP-Max further lowers the expense of time and space.

关键词： data mining frequent pattern the maximal frequent pattern Unid _ FP-tree conditional Unid _ FP-tree

来源：评论

学校读者我要写书评

暂无评论

Algebraic Independence Measures for the Values of Mahler Type Functions

引用

Chinese Quarterly Journal of Mathematics 2006年第4期21卷 567-576页

作者： WANG Tian-qin LIU Hua-ke Institute of Data and Knowledge Engineering Henan University Kaifeng 475001 China College of Mathematics and Information Science Henan University Kaifeng 475001 China

In this paper, we give the algebraic independence measures for the values ofMahler type functions in complex number field and p-adic number field, respectively.

关键词： algebraic independence measure Mahler type function p-adic number field

来源：评论

学校读者我要写书评

暂无评论

Recent trends in data Mining (DM): Document Clustering of DM Publications

Recent trends in Data Mining (DM): Document Clustering of DM...

引用

International Conference on Services Systems and Services Management, ICSSSM

作者： Yi Peng Gang Kou Zhengxin Chen Yong Shi Peter Kiewit Institute ofInformation Science Technology & Engineering University of Nebraska Omaha NE USA Chinese Academy of Sciences Research Center on Data Technology & Knowledge Economy Chinese Academy of Sciences Beijing China

data mining (DM) brings knowledge and theories from several fields including databases, machine learning, optimization, statistics, and data visualization and has been applied to various real-life applications. A large amount of data mining articles have been published. The goal of this study is to establish an overview of the past and current data mining research activities from the title and abstract more than 1400 textual documents collected from premier data mining journals and conference proceedings. Specifically, this study applied document clustering approaches to determine which subjects had been studied over the last several years, which subjects are currently popular, and describe the longitudinal changes of data mining publications

关键词： Delta modulation data mining Machine learning Conference proceedings IEL data engineering Visual databases Statistics data visualization Software libraries

来源：评论

学校读者我要写书评

暂无评论

Application of Clustering Methods to Health Insurance Fraud Detection

Application of Clustering Methods to Health Insurance Fraud ...

引用

International Conference on Services Systems and Services Management, ICSSSM

作者： Yi Peng Gang Kou Alan Sabatka Zhengxin Chen Deepak Khazanchi Yong Shi Peter Kiewit Institute of Information Science Technology & Engineering University of Nebraska Omaha Omaha NE USA Mutual of Omaha Omaha NE USA Chinese Academy of Sciences Research Center on Data Technology & Knowledge Economy Chinese Academy of Sciences Beijing China

Health insurance fraud detection is an important and challenging task. Traditionally, insurance companies use human inspections and heuristic rules to detect fraud. As the size of databases increases, the traditional approaches may miss a great portion of fraud for two main reasons. First, it is impossible to detect all health care fraud by manual inspection over large databases. Second, new types of health care fraud emerge constantly. SQL operations based on heuristic rules cannot identify those new emerging fraud schemes. Such a situation demands more sophisticated analytical methods and techniques that are capable of detecting fraud activities from large databases. The goal of this paper is to understand and detect suspicious health care frauds from large databases using clustering technique. Specifically, this paper applies two clustering methods, SAS EM and CLUTO, to a large real-life health insurance dataset and compares the performances of these two methods

关键词： Clustering methods Insurance Medical services Inspection Synthetic aperture sonar Humans data mining Spatial databases Cities and towns Input variables

来源：评论

学校读者我要写书评

暂无评论

Semantics, Web and Mining: Preface

Lecture Notes in Computer Science (including subseries Lectu...

引用

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2006年 4289 LNAI卷 v-vi页

作者： Berendt, Bettina Hotho, Andreas Mladenič, Dunja Semeraro, Giovanni Spiliopoulou, Myra Stumme, Gerd Van Someren, Maarten Ackermann, Markus Grobelnik, Marko Svátek, Vojtěch Institute of Information Systems Humboldt University Berlin Germany Knowledge and Data Engineering Group University of Kassel Germany J. Stefan Institute Ljubljana Slovenia Department of Informatics University of Bari Italy Faculty of Computer Science Otto-von-Guericke-Univ. Magdeburg Germany Informatics Institute University of Amsterdam Netherlands Dept. of Natural Language Processing Institute for Computer Science University of Leipzig Germany University of Economics Prague Czech Republic

来源：评论

学校读者我要写书评

暂无评论

A Depth-first Algorithm of Finding All Association Rules Generated by a Frequent Itemset

引用

Journal of Donghua University(English Edition) 2006年第6期000卷

作者： WU Kun JIANG Bao-qing WEI Qing WU Kun(Institute of Data and Knowledge Engineering Henan University Kaifeng 475001 The Personnel Department Zhengzhou Institute of Aeronautical Industry ManagementZhengzhou 450000) JIANG Bao-qing(Institute of Data and Knowledge Engineering Henan University Kaifeng 475001) WEI Qing(The Computer Science Department Henan University of Finance and Economics Zhengzhou 450000)

The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the *** show GRSET algorithm to be practicable and efficient.

关键词： association rule frequent itemset breath-first depth-first consequent

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：