检索结果-内蒙古大学图书馆

International Conference on Mechatronics and Semiconductor Materials (ICMSCM 2013)

作者： Wang, Yini Chongqing Business Vocat Coll Chongqing 400030 Peoples R China

Taking data mining technologies as the key, with the analysis of electronic commerce, this paper studies deeply on the implementation of data mining system that is electronic commerce-oriented.

ISBN: (纸本)9783037859391

Taking data mining technologies as the key, with the analysis of electronic commerce, this paper studies deeply on the implementation of data mining system that is electronic commerce-oriented.

关键词： Data mining Electronic Commerce mining algorithm

来源：评论

学校读者我要写书评

暂无评论

Research of Commonly Used Association Rules mining algorithm in Data mining

Research of Commonly Used Association Rules Mining Algorithm...

引用

2010 The 3rd International Conference on Computational Intelligence and Industrial Application (PACIIA2010)

作者： Ruowu Zhong Institute of Computer Shaoguan University Shaoguan,Guangdong Province,China Huiping Wang Institute of Computer Shaoguan University Shaoguan,Guangdong Province,China

This paper introduces the concept of data mining and its an important branch association rules,describes the basic concept of association rules,the basic model of mining association rules;introduces the classical algorithm of association rules,and then classified discusses the association rules mining from several angles such as width,depth,partition,sampling and incremental updating. Finally,this paper prospects the association rules mining.

关键词： data mining association rules frequent itemsets mining algorithm

来源：评论

学校读者我要写书评

暂无评论

Graph Hashing and Factorization for Fast Graph Stream Classification 13

Graph Hashing and Factorization for Fast Graph Stream Classi...

引用

22nd ACM International Conference on Information and Knowledge Management (CIKM)

作者： Guo, Ting Chi, Lianhua Zhu, Xingquan Univ Technol Fac Engn & Info Tech QCIS Ctr Sydney NSW 2007 Australia

ISBN: (纸本)9781450322638

Graph stream classification concerns building learning models from continuously growing graph data, in which an essential step is to explore subgraph features to represent graphs for effective learning and classification. When representing a graph using subgraph features, all existing methods employ coarse-grained feature representation, which only considers whether or not a subgraph feature appears in the graph. In this paper. we propose a fine-grained graph factorization approach for Fast Graph Stream Classification (FGSC). Our main idea is to find a set of cliques as feature base to represent each graph as a linear combination of the base cliques. To achieve this goal, we decompose each graph into a number of cliques and select discriminative cliques to generate a transfer matrix called Clique Set Matrix (M). By using M as the base for formulating graph factorization, each graph is represented in a vector space with each element denoting the degree of the corresponding subgraph feature related to the graph, so existing supervised learning algorithms can be applied to derive learning models for graph classification.

关键词： Graph stream matrix factorization mining algorithm

来源：评论

学校读者我要写书评

暂无评论

An improved association rules mining method

引用

EXPERT SYSTEMS WITH APPLICATIONS 2012年第1期39卷 1362-1374页

作者： Liu, Xiaobing Zhai, Kun Pedrycz, Witold Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2G7 Canada Dalian Univ Technol Fac Management Dalian 116023 Peoples R China Polish Acad Sci Syst Res Inst PL-01447 Warsaw Poland

mining maximal frequent itemsets is of paramount relevance in many of data mining applications. The "traditional" algorithms address this problem through scanning databases many times. The latest research has already focused on reducing the number of scanning times of databases and then decreasing the number of accessing times of I/O resources in order to improve the overall mining efficiency of maximal frequent itemsets of association rules. In this paper, we present a form of the directed itemsets graph to store the information of frequent itemsets of transaction databases, and give the trifurcate linked list storage structure of directed itemsets graph. Furthermore, we develop the mining algorithm of maximal frequent itemsets based on this structure. As a result, one realizes scanning a database only once, and improves storage efficiency of data structure and time efficiency of mining algorithm. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Association rule Maximal frequent itemsets Directed itemsets graph Trifurcate linked list storage structure mining algorithm

来源：评论

学校读者我要写书评

暂无评论

Network Topology Constraint Based Transaction Separation and mining algorithm of Telecom Alarm

Network Topology Constraint Based Transaction Separation and...

引用

International Symposium on Knowledge Acquisition and Modeling

作者： Chen, Jun Zhang, Bin Li, Guohui Beijing Univ Posts & Telecommun Pattern Recognit & Intelligent Syst Lab Beijing 100088 Peoples R China

ISBN: (纸本)9781424435296

The efficiency of alarm mining in large scale network is a hot topic in research area of fault location. Many projects have been utilized to improve it and some advance has been achieved, but it is still not very satisfied. Large scale telecom system daily generates large numbers of original alarm records and many of them are redundant information, actually useful information for fault location is only a small part. So in order to increase efficiency of alarm mining, we propose a solution called network topology constraint based transaction separation in this paper and we also compare it with the method of adding topology constraint into mining algorithms. The experiments show that separating transaction with network topology constraint deletes a huge number of redundant alarm information and incorrect transaction sets before executing mining algorithms, therefore, it is can be more efficient and precise than topology constraint based mining algorithm, which filters erroneous frequent sub-patterns during algorithm execution.

关键词： network topology constraint alarm mining transaction separation telecom alarm mining algorithm

来源：评论

学校读者我要写书评

暂无评论

Network Topology Constraint Based Transaction Separation and mining algorithm of Telecom Alarm

Network Topology Constraint Based Transaction Separation and...

引用

2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop(KAM 2008)

作者： Jun Chen Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications (BUPT) Beijing,ChinaBin Zhang,Guohui Li Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications (BUPT) Beijing,China

The efficiency of alarm mining in large scale network is a hot topic in research area of fault *** projects have been utilized to improve it and some advance has been achieved,but it is still not very *** scale telecom system daily generates large numbers of original alarm records and many of them are redundant information,actually useful information for fault location is only a small *** in order to increase efficiency of alarm mining,we propose a solution called network topology constraint based transaction separation in this paper and we also compare it with the method of adding topology constraint into mining *** experiments show that separating transaction with network topology constraint deletes a huge number of redundant alarm information and incorrect transaction sets before executing mining algorithms,therefore,it is can be more efficient and precise than topology constraint based mining algorithm,which filters erroneous frequent sub-patterns during algorithm execution.

关键词： network topology constraint alarm mining transaction separation telecom alarm mining algorithm

来源：评论

学校读者我要写书评

暂无评论

Composable Correlation mining of Cloud Service in Cloud Manufacturing

Composable Correlation Mining of Cloud Service in Cloud Manu...

引用

IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Guo, Hua Zhang, Lin Tao, Fei Ren, Zhiyun Luo, Yongliang Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781457707391

The emergence of cloud manufacturing (CMfg) provides a new opportunity for the change of manufacturing towards service-oriented model. Cloud service composition (CSC), which can realize the added value of cloud service (CS), is the core to implement CMfg. Since there always exist correlations among CSs, especially composable correlation (CoC), which can affect the construction of CSC path. Hence, how to mine the CoC among CSs and judge which kind of CoC between them is a key issue. This paper presents the formalized description for CoC, and designs decision algorithms to judge CoCs between CSs based on bipartite graph. The case study illustrates the application of proposed algorithms.

关键词： Composabale correlation mining algorithm cloud service composition cloud manufacturing (CMfg)

来源：评论

学校读者我要写书评

暂无评论

A computational model for predicting the transport of compounds by ABCC2

引用

Journal of Cheminformatics 2012年第1期4卷 1-1页

作者： Marta Pinto Gerhard F Ecker Department of Medicinal Chemistry University of Vienna Vienna 1090 Austria

来源：评论

学校读者我要写书评

暂无评论

The construction method of knowledge discovery theory system based on cognitive

The construction method of knowledge discovery theory system...

引用

Pacific-Asia Conference on Circuits, Communications and System

作者： Yang, Bingru Wang, Lijun Department of Information Engineering School University of Science and Technology Beijing 100083 China

ISBN: (纸本)9781457708565

The mainstream of development in knowledge discovery is researching on new high-performance and high- scalability mining algorithm. In fact, the research of process model and inner mechanism is more important, which have got enough attention. This paper proposed a new independent knowledge discovery system framework, which combines those three elements: algorithm, model and mechanism. In essence, it derives the systematic method from the general algorithms. Experimental results and researches show that this research can resolve some realistic problems such as timely knowledge databases maintaining and so on;by exposing the essence, regularity and complexity of KD, it would react on the mainstream, and become one available route of constituting the KD theory system... © 2011 IEEE.

关键词： Accuracy algorithm design and analysis Data mining Databases Heuristic algorithms Proteins Psychology data mining independent knowledge discovery system framework knowledge discovery theory system mining algorithm timely knowledge databases

来源：评论

学校读者我要写书评

暂无评论

mining dynamic association rules with comments

引用

KNOWLEDGE AND INFORMATION SYSTEMS 2010年第1期23卷 73-98页

作者： Shen, Bin Yao, Min Wu, Zhaohui Gao, Yunjun Zhejiang Univ Coll Comp Sci & Technol Hangzhou 310027 Peoples R China Zhejiang Univ Ningbo Inst Technol Ningbo 315100 Zhejiang Peoples R China Singapore Management Univ Sch Informat Syst Singapore 178902 Singapore

In this paper, we study a new problem of mining dynamic association rules with comments (DAR-C for short). A DAR-C contains not only rule itself, but also its comments that specify when to apply the rule. In order to formalize this problem, we first present the expression method of candidate effective time slots, and then propose several definitions concerning DAR-C. Subsequently, two algorithms, namely ITS2 and EFP-Growth2, are developed for handling the problem of mining DAR-C. In particular, ITS2 is an improved two-stage dynamic association rule mining algorithm, while EFP-Growth2 is based on the EFP-tree structure and is suitable for mining high-density mass data. Extensive experimental results demonstrate that the efficiency and scalability of our proposed two algorithms (i.e., ITS2 and EFP-Growth2) on DAR-C mining tasks, and their practicability on real retail dataset.

关键词： Dynamic association rule Comment Support vector Confidence vector mining algorithm

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：