检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

29 篇 会议
6 篇 期刊文献
4 册 图书

馆藏范围

39 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

15 篇 工学
- 14 篇 计算机科学与技术...
- 8 篇 软件工程
- 6 篇 信息与通信工程
- 4 篇 材料科学与工程（可...
- 2 篇 电气工程
- 2 篇 控制科学与工程
- 1 篇 农业工程
8 篇 理学
- 7 篇 数学
- 1 篇 系统科学
- 1 篇 统计学（可授理学、...
3 篇 管理学
- 2 篇 图书情报与档案管...
- 1 篇 管理科学与工程(可...
1 篇 农学
- 1 篇 作物学

主题

13 篇 knowledge engine...
8 篇 fuzzy sets
8 篇 clustering algor...
7 篇 prototypes
7 篇 artificial intel...
6 篇 computer science
6 篇 data analysis
4 篇 data engineering
4 篇 design engineeri...
4 篇 partitioning alg...
3 篇 information syst...
3 篇 neural networks
3 篇 database managem...
3 篇 covariance matri...
3 篇 computational mo...
3 篇 costs
3 篇 humans
3 篇 shape
2 篇 euclidean distan...
2 篇 zinc

机构

9 篇 department of kn...
4 篇 otto von guerick...
4 篇 faculty of compu...
3 篇 department of kn...
3 篇 european centre ...
3 篇 fachbereich math...
2 篇 fakultät für ele...
2 篇 department of kn...
2 篇 dipartimento di ...
2 篇 department of kn...
2 篇 department of kn...
2 篇 cognitive comput...
1 篇 dept. of natural...
1 篇 university of sc...
1 篇 computer science...
1 篇 school of comput...
1 篇 research center ...
1 篇 dept. of compute...
1 篇 dept. informatio...
1 篇 university of il...

作者

12 篇 r. kruse
9 篇 kruse rudolf
9 篇 c. borgelt
9 篇 rudolf kruse
6 篇 borgelt christia...
3 篇 c. doring
3 篇 h. timm
3 篇 xiaomeng wang
2 篇 a. nurnberger
2 篇 pasi gabriella
2 篇 frank hoffmann
2 篇 eyke hüllermeier
2 篇 christian borgel...
2 篇 alonso jose mari...
1 篇 savelonas m.a.
1 篇 spiliopoulou myr...
1 篇 michael r. berth...
1 篇 vojtěch svátek
1 篇 hüllermeier eyke
1 篇 nguyen h.-d.

语言

39 篇 英文

检索条件"机构=Department of Knowledge Processing and Language Engineering"

共 39 条记录，以下是21-30 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Effects of Irrelevant Attributes in Fuzzy Clustering

Effects of Irrelevant Attributes in Fuzzy Clustering

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： C. Doring C. Borgelt R. Kruse Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

In fuzzy clustering soft cluster partitions are formed based on the similarity of data points to the respective cluster prototypes. Similarity is defined in terms of simultaneous closeness regarding all attributes. In some applications the values of many attributes have been measured, but a natural clustering, if it exists, occurs within a (small) subset of attributes. The remaining dimensions can be considered irrelevant. They can obscure an existing grouping and make it harder to discover the cluster structure. In probabilistic fuzzy clustering irrelevant attributes can lead to coincidental cluster centers in the worst case. We study this effect in detail as well as the robustness of different similarity functions and their possible parameterizations against irrelevant input dimensions. Empirical evidence is given for the different properties of the membership functions

关键词： Fuzzy sets Clustering algorithms Partitioning algorithms Iterative algorithms Shape measurement Data engineering Design engineering knowledge engineering Prototypes Robustness

来源：评论

学校读者我要写书评

暂无评论

Fuzzy frequent pattern discovering based on recursive elimination

Fuzzy frequent pattern discovering based on recursive elimin...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Xiaomeng Wang C. Borgelt R. Kruse Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

Real life transaction data often miss some occurrences of items that are actually present. As a consequence some potentially interesting frequent patterns cannot be discovered, since with exact matching the number of supporting transactions may be smaller than the user-specified minimum. In order to allow approximate matching during the mining process, we propose an approach based on transaction editing. Our recursive algorithm relies on a step by step elimination of items from the transaction database together with a recursive processing of transaction subsets. This algorithm works without complicated data structures and allows us to find fuzzy frequent patterns easily.

关键词： Costs Transaction databases Pattern matching Data structures Data engineering knowledge engineering Computer science Delay effects Association rules Fuzzy sets

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Learning Vector Quantization with Size and Shape Parameters

Fuzzy Learning Vector Quantization with Size and Shape Param...

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： C. Borgelt A. Nurnberger R. Kruse Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

We study an extension of fuzzy learning vector quantization that draws on ideas from the more sophisticated approaches to fuzzy clustering, enabling us to find fuzzy clusters of ellipsoidal shape and differing size with a competitive learning scheme. This approach may be seen as a kind of online fuzzy clustering, which can have advantages w.r.t. the execution time of the clustering algorithm. We demonstrate the usefulness of our approach by applying it to document collections, which are, in general, difficult to cluster due to the high number of dimensions and the special distribution characteristics of the data

关键词： Vector quantization Shape Clustering algorithms Fuzzy sets Covariance matrix Partitioning algorithms knowledge engineering Maximum likelihood estimation Web pages

来源：评论

学校读者我要写书评

暂无评论

MoSS: A program for molecular substructure mining

MoSS: A program for molecular substructure mining

引用

1st International Workshop on Open Source Data Mining: Frequent Pattern Mining Implementations, OSDM 2005, held in conjunction with the 11th ACM SIGKDD International Conference on knowledge Discovery and Data Mining

作者： Borgelt, Christian Meinl, Thorsten Berthold, Michael Dept. of Knowledge Processing and Language Engineering University of Magdeburg Universitätsplatz 2 39106 Magdeburg Germany Computer Science Department 2 University of Erlangen-Nuremberg Martenstraße 3 91058 Erlangen Germany Dept. of Computer and Information Science University of Konstanz 78457 Konstanz Germany

ISBN: (纸本)1595932100

Molecular substructure mining is currently an intensively studied research area. In this paper we present an implementation of an algorithm for finding frequent substructures in a set of molecules, which may also be used to find substructures that discriminate well between a focus and a complement group. In addition to the basic algorithm, we discuss advanced pruning techniques, demonstrating their effectiveness with experiments on two publicly available molecular data sets, and briefly mention some other extensions. Copyright 2005 ACM.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fuzzy clustering of quantitative and qualitative data

Fuzzy clustering of quantitative and qualitative data

引用

Conference of the North American Fuzzy Information processing Society - NAFIPS

作者： C. Doring C. Borgelt R. Kruse Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

In many applications the objects to cluster are described by quantitative as well as qualitative features. A variety of algorithms has been proposed for unsupervised classification if fuzzy partitions and descriptive cluster prototypes are desired. However, most of these methods are designed for data sets with variables measured in the same scale type (only categorical, or only metric). We propose a new fuzzy clustering approach based on a probabilistic distance measure. Thus a major drawback of present methods can be avoided which ties in the vulnerability to favor one type of attributes.

关键词： Clustering algorithms Prototypes Partitioning algorithms Data analysis Data engineering Design engineering knowledge engineering Design methodology Frequency Fuzzy sets

来源：评论

学校读者我要写书评

暂无评论

Adaptable Markov models in industrial planning

Adaptable Markov models in industrial planning

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： J. Gebhardt F. Rugheimer H. Detmer R. Kruse Intelligent Systems Consulting Celle Germany Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany Volkswagen Group Wolfsburg Germany

A significant number of scientific and economic problems is characterised by a large number of interrelated variables. But with larger variable number, the domain under consideration may grow fast, so that analyses and reasoning become increasingly difficult. Graphical models allow to represent the combined distributions compactly and are suitable for dealing with uncertain and incomplete information. We describe their application to a problem of industrial planning. We also demonstrate how the iterative planning process can be supported by allowing the users to adapt the model using revision and updating operators. Moreover we discuss the problem of inconsistent inputs.

关键词： Graphical models Educational institutions Algae Intelligent systems knowledge engineering Process planning Data preprocessing Bayesian methods Markov random fields Probability distribution

来源：评论

学校读者我要写书评

暂无评论

Speeding up fuzzy clustering with neural network techniques

Speeding up fuzzy clustering with neural network techniques

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： C. Borgelt R. Kruse Research Group Neural Networks and Fuzzy Systems Department of Knowledge Processing and Language Engineering School of Computer Science Otto-von-Guericke University of Magdeburg Germany

We explore how techniques that were developed to improve the training process of artificial neural networks can be used to speed up fuzzy clustering. The basic idea of our approach is to regard the difference between two consecutive steps of the alternating optimization scheme of fuzzy clustering as providing a gradient, which may be modified in the same way as the gradient of neural network back-propagation is modified in order to improve training. Our experimental results show that some methods actually lead to a considerable acceleration of the clustering process.

关键词： Fuzzy neural networks Neural networks Artificial neural networks Backpropagation Fuzzy systems knowledge engineering Computer science Electronic mail Acceleration Multilayer perceptrons

来源：评论

学校读者我要写书评

暂无评论

A modification to improve possibilistic fuzzy cluster analysis

A modification to improve possibilistic fuzzy cluster analys...

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： H. Timm R. Kruse Department of Knowledge Processing and Language Engineering Otto von Guericke University Magdeburg Magdeburg Germany

We explore an approach to possibilistic fuzzy clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other. We develop this approach for the possibilistic fuzzy c-means algorithm and the Gustafson-Kessel algorithm.

关键词： Clustering algorithms Prototypes knowledge engineering Fuzzy sets Humans Zinc Euclidean distance Covariance matrix

来源：评论

学校读者我要写书评

暂无评论

An extension of partially supervised fuzzy cluster analysis

An extension of partially supervised fuzzy cluster analysis

引用

Conference of the North American Fuzzy Information processing Society - NAFIPS

作者： H. Timm F. Klawonn R. Kruse Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Germany Department of Computer Science University of Applied Sciences Braunschweig Wolfenbuttel Germany

We propose an approach to handling class information in fuzzy cluster analysis, where a class can consist of several clusters. The approach is based on a penalty term for clusters comprising several clusters.

关键词： Prototypes Information analysis Clustering algorithms Fuzzy sets Zinc Computer science Equations Shape

来源：评论

学校读者我要写书评

暂无评论

An empirical investigation of the k2 metric 6

引用

6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2001

作者： Borgelt, Christian Kruse, Rudolf Department of Knowledge Processing and Language Engineering Otto-von-Guericke-University of Magdeburg Universitatsplatz 2 MagdeburgD-39106 Germany

ISBN: (纸本)9783540424642

The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions on the values of an attribute for each possible instantiation of its parent attributes. This assumption introduces a tendency to select simpler network structures. In this paper we modify the K2 metric in three different ways, introducing a parameter by which the strength of this tendency can be controlled. Our experiments with the ALARM network [2] and the BOBLO network [17] suggest that—somewhat contrary to our expectations—a slightly stronger tendency towards simpler structures may lead to even better results. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共4页 << < 1 2 3 4 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：