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

91 篇 会议
13 册 图书
2 篇 期刊文献

馆藏范围

106 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

77 篇 工学
- 71 篇 计算机科学与技术...
- 41 篇 电气工程
- 19 篇 软件工程
- 5 篇 信息与通信工程
- 4 篇 仪器科学与技术
- 2 篇 动力工程及工程热...
- 2 篇 控制科学与工程
- 2 篇 化学工程与技术
- 2 篇 生物医学工程（可授...
- 1 篇 机械工程
- 1 篇 光学工程
- 1 篇 生物工程
39 篇 医学
- 39 篇 临床医学
19 篇 理学
- 14 篇 数学
- 5 篇 统计学（可授理学、...
- 3 篇 系统科学
- 2 篇 物理学
- 2 篇 化学
- 1 篇 生物学
10 篇 管理学
- 10 篇 图书情报与档案管...
1 篇 经济学
- 1 篇 应用经济学
1 篇 法学
- 1 篇 社会学
1 篇 艺术学
- 1 篇 设计学（可授艺术学...

主题

23 篇 machine learning
21 篇 pattern recognit...
12 篇 data mining
11 篇 training
10 篇 data models
9 篇 feature extracti...
9 篇 artificial intel...
7 篇 deep learning
7 篇 benchmark testin...
6 篇 support vector m...
6 篇 neural networks
6 篇 data mining and ...
6 篇 visualization
6 篇 semantics
5 篇 learning systems
5 篇 information syst...
5 篇 computer vision
4 篇 image segmentati...
4 篇 federated learni...
4 篇 measurement

机构

2 篇 univ elect sci &...
2 篇 chengdu univ tec...
2 篇 univ kaiserslaut...
2 篇 iee sa bissen lu...
1 篇 iit jodhpur jodh...
1 篇 kazan federal un...
1 篇 department of co...
1 篇 institute of inf...
1 篇 department of ch...
1 篇 department of fo...
1 篇 technische unive...
1 篇 key laboratory o...
1 篇 inst sci & techn...
1 篇 lg display
1 篇 faculty of elect...
1 篇 univ bonn bonn
1 篇 national laborat...
1 篇 sun yat sen univ...
1 篇 univ grenoble al...
1 篇 ufr mim universi...

作者

3 篇 li fan
3 篇 hu xiaonan
3 篇 liu qihe
2 篇 pudi vikram
2 篇 de-shuang huang
2 篇 duoqian miao
2 篇 hepu deng
2 篇 ye mao
2 篇 stricker didier
2 篇 fu lee wang
2 篇 da cruz steve di...
2 篇 shuigeng zhou
2 篇 cheng xianqiong
2 篇 songmao zhang
2 篇 george karypis
2 篇 stifter thomas
2 篇 jingsheng lei
2 篇 taetz bertram
1 篇 wil m. p. van de...
1 篇 seyed tabatabaei...

语言

104 篇 英文
1 篇 其他
1 篇 中文

检索条件"任意字段=8th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2012"

共 106 条记录，以下是71-80 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：

Proximity-graph instance-based learning, support vector machines, and high dimensionality: An empirical comparison

Proximity-graph instance-based learning, support vector mach...

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Toussaint, Godfried T. Berzan, Constantin Faculty of Science New York University Abu Dhabi Abu Dhabi United Arab Emirates Department of Computer Science Tufts University Medford MA 02155 United States

ISBN: (纸本)9783642315367

Previous experiments with low dimensional data sets have shown that Gabriel graph methods for instance-based learning are among the best machine learning algorithms for pattern classification applications. However, as the dimensionality of the data grows large, all data points in the training set tend to become Gabriel neighbors of each other, bringing the efficacy of this method into question. Indeed, it has been conjectured that for high-dimensional data, proximity graph methods that use sparser graphs, such as relative neighbor graphs (RNG) and minimum spanning trees (MST) would have to be employed in order to maintain their privileged status. Here the performance of proximity graph methods, in instance-based learning, that employ Gabriel graphs, relative neighborhood graphs, and minimum spanning trees, are compared experimentally on high-dimensional data sets. these methods are also compared empirically against the traditional k-NN rule and support vector machines (SVMs), the leading competitors of proximity graph methods. © 2012 Springer-Verlag.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Content independent metadata production as a machine learning problem

Content independent metadata production as a machine learnin...

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Changuel, Sahar Labroche, Nicolas Université Pierre et Marie Curie - Paris 6 CNRS UMR7606 France

ISBN: (纸本)9783642315367

Metadata provide a high-level description of digital library resources and represent the key to enable the discovery and selection of suitable resources. However the growth in size and diversity of digital collections makes manual metadata extraction an expensive task. this paper proposes a new content independent method to automatically generate metadata in order to characterize resources in a given learning objects repository. the key idea is to rely on few existing metadata to learn predictive models of metadata values. the proposed method is content independent and handles resources in different formats: text, image, video, Java applet, etc. Two classical machine learning approaches are studied in this paper: in the first approach a supervised machine learning technique classify each value of a metadata field to be predicted according to the other a-priori filled metadata fields. the second approach used the FP-Growth algorithm to discover relationships between the different metadata fields as association rules. Experiments on two well-known educational data repositories show that both approaches can enhance metadata extraction and can even fill subjective metadata fields that are difficult to extract from the content of a resource, such as the difficulty of a resource. © 2012 Springer-Verlag.

关键词： Metadata

来源：评论

学校读者我要写书评

暂无评论

machine learning-based classification of encrypted internet traffic

Machine learning-based classification of encrypted internet ...

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Seyed Tabatabaei, Talieh Adel, Mostafa Karray, Fakhri Kamel, Mohamed University of Waterloo Waterloo ON Canada

ISBN: (纸本)9783642315367

Peer-to-peer (P2P) networking has introduced a major shift in the application and traffic mix of the Internet and established itself as the main driver of increasing traffic volume. the high requirements of some P2P applications result in network operational issues: these applications consume vast amounts of network resources and can prevent mission critical applications from accessing the network. therefore the ability to correctly identify them can be crucial for many network management and measurement tasks. In this paper some flow-based statistical features of Internet traffic are investigated in order to detect P2P traffic. We propose a system to identify the BT traffic, which is one of the most popular and problematic P2P applications using support vector machines. the accuracy of 94.5% was achieved for recognizing encrypted traffic which is a very promising result. © 2012 Springer-Verlag.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Multi-label image annotation based on neighbor pair correlation chain

Multi-label image annotation based on neighbor pair correlat...

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Jiang, Guang Liu, Xi Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China Information Technology Laboratory Fujitsu Research and Development Center Co. Ltd. Beijing 100025 China

ISBN: (纸本)9783642315367

Image annotation plays an important role in content-based image understanding, various machine learning methods have been proposed to solve this problem. In this paper, label correlation is considered as an undirected bipartite graph, in which each label are correlated by some common hidden topics. As a result, given a label, random walk with restart on the graph supplies a most related label, repeating this precedure leads to a label chain, which keep each adjacent labels pair correlated as maximally as possible. We coordinate the labels chain with its respective classifier training on bottom feature, and guide a classifier chain to annotate an image. the experiment illustrates that our method outperform both the baseline and another popular method. © 2012 Springer-Verlag.

关键词： learning systems

来源：评论

学校读者我要写书评

暂无评论

A pattern discovery model for effective text mining

A pattern discovery model for effective text mining

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Pipanmaekaporn, Luepol Li, Yuefeng School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane QLD Australia

ISBN: (纸本)9783642315367

the quality of extracted features is the key issue to text mining due to the large number of terms, phrases, and noise. Most existing text mining methods are based on term-based approaches which extract terms from a training set for describing relevant information. However, the quality of the extracted terms in text documents may be not high because of lot of noise in text. For many years, some researchers make use of various phrases that have more semantics than single words to improve the relevance, but many experiments do not support the effective use of phrases since they have low frequency of occurrence, and include many redundant and noise phrases. In this paper, we propose a novel pattern discovery approach for text mining. this approach first discovers closed sequential patterns in text documents for identifying the most informative contents of the documents and then utilise the identified contents to extract useful features for text mining. We develop a novel fusion method based on Dempster-Shafer's evidential reasoning which allows to combine the pieces of document to discover the knowledge (features). To evaluate the proposed approach, we adopt the feature extraction method for information filtering (IF). the experimental results conducted on Reuters Corpus Volume 1 and TREC topics confirm that the proposed approach could achieve excellent performance. © 2012 Springer-Verlag.

关键词： Information filtering

来源：评论

学校读者我要写书评

暂无评论

Clustering data stream by a sub-window approach using DCA

Clustering data stream by a sub-window approach using DCA

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Ta, Minh thuy Le thi, Hoai An Boudjeloud-Assala, Lydia UFR MIM University of Lorraine Ile du Saulcy 57045 Metz France

ISBN: (纸本)9783642315367

data stream is one emerging topic of data mining, it concerns many applications involving large and temporal data sets such as telephone records data, banking data, multimedia data,... For mining of such data, one crucial strategy is analysis of packet data. In this paper, we are interested in an exploratory analysis of strategies for clustering data stream based on a sub-window approach and an efficient clustering algorithm called DCA (Difference of Convex functions Algorithm). Our approach consists of separating the data on different sub-windows and then apply a DCA clustering algorithm on each sub-window. Two clustering strategies are investigated: global clustering (on the whole data set) and independent local clustering (i.e. clustering independently on each sub-window). Our aims are study: (1) the efficiency of the independent local clustering, and (2) the adequation of local clustering and global clustering based on the same DCA clustering algorithm. Comparative experiments with clustering data stream using K-Means, a standard clustering method, on different data sets are presented. © 2012 Springer-Verlag.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

mining ranking models from dynamic network data

Mining ranking models from dynamic network data

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Macchia, Lucrezia Ceci, Michelangelo Malerba, Donato Dipartimento di Informatica Università degli Studi di Bari via Orabona 4 70126 Bari Italy

ISBN: (纸本)9783642315367

In recent years, improvement in ubiquitous technologies and sensor networks have motivated the application of data mining techniques to network organized data. Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation where the value of a variable at a given node depends on the values of variables at the nodes it is connected with. this phenomenon is a direct violation of the assumption that data are independently and identically distributed (i.i.d.). At the same time, it offers the unique opportunity to improve the performance of predictive models on network data, as inferences about one entity can be used to improve inferences about related entities. In this work, we propose a method for learning to rank from network data when data distribution may change over time. the learned models can be used to predict the ranking of nodes in the network for new time periods. the proposed method modifies the SVMRank algorithm in order to emphasize the importance of models learned in time periods during which data follow a data distribution that is similar to that observed in the new time period. We evaluate our approach on several real world problems of learning to rank from network data, coming from the area of sensor networks. © 2012 Springer-Verlag.

关键词： Sensor networks

来源：评论

学校读者我要写书评

暂无评论

Investigating usage of text segmentation and inter-passage similarities to improve text document clustering

Investigating usage of text segmentation and inter-passage s...

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Paliwal, Shashank Pudi, Vikram Center for Data Engineering International Institute of Information Technology Hyderabad India

ISBN: (纸本)9783642315367

Measuring inter-document similarity is one of the most essential steps in text document clustering. Traditional methods rely on representing text documents using the simple Bag-of-Words (BOW) model. A document is an organized structure consisting of various text segments or passages. Such single term analysis of the text treats whole document as a single semantic unit and thus, ignores other semantic units like sentences, passages etc. In this paper, we attempt to take advantage of underlying subtopic structure of text documents and investigate whether clustering of text documents can be improved if text segments of two documents are utilized, while calculating similarity between them. We concentrate on examining effects of combining suggested inter-document similarities (based on inter-passage similarities) with traditional inter-document similarities following a simple approach for the same. Experimental results on standard data sets suggest improvement in clustering of text documents. © 2012 Springer-Verlag.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

Hot deck methods for imputing missing data: the effects of limiting donor usage

Hot deck methods for imputing missing data: The effects of l...

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Joenssen, Dieter William Bankhofer, Udo Technische Universität Ilmenau Fachgebiet für Quantitative Methoden Ilmenau Germany

ISBN: (纸本)9783642315367

Missing data methods, within the data mining context, are limited in computational complexity due to large data amounts. Amongst the computationally simple yet effective imputation methods are the hot deck procedures. Hot deck methods impute missing values within a data matrix by using available values from the same matrix. the object, from which these available values are taken for imputation within another, is called the donor. the replication of values leads to the problem, that a single donor might be selected to accommodate multiple recipients. the inherent risk posed by this is that too many, or even all, missing values may be imputed with the values from a single donor. To mitigate this risk, some hot deck variants limit the amount of times any one donor may be selected for donating its values. this inevitably leads to the question under which conditions such a limitation is sensible. this study aims to answer this question though an extensive simulation. the results show rather clear differences between imputations by hot deck methods in which the donor limit was varied. In addition to these differences, influencing factors are identified that determine whether or not a donor limit is sensible. © 2012 Springer-Verlag.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

A new learning structure heuristic of Bayesian Networks from data

A new learning structure heuristic of Bayesian Networks from...

引用

8th international conference on machine learning and data mining in pattern recognition, mldm 2012

作者： Bouhamed, Heni Masmoudi, Afif Lecroq, thierry Rebaï, Ahmed University of Rouen LITIS EA 4108 1 rue Thomas Becket 76821 Mont-Saint-Aignan Cedex France Department of Mathematics Faculty of Science of Sfax Soukra B.P 802 Sfax Tunisia Bioinformatics Unit Centre of Biotechnologie of Sfax 3018 Sfax Tunisia

ISBN: (纸本)9783642315367

Nowadays, Bayesian Networks (BNs) have constituted one of the most complete, self-sustained and coherent formalisms useful for knowledge acquisition, representation and application through computer systems. Yet, the learning of these BNs structures from data represents a problem classified at an NP-hard range of difficulty. As such, it has turned out to be the most exciting challenge in the learning machine area. In this context, the present work's major objective lies in setting up a further solution conceived to be a remedy for the intricate algorithmic complexity problems imposed during the learning of BN-structure through a massively-huge data backlog. Our present work has been constructed according to the following framework;on a first place, we are going to proceed by defining BNs and their related problems of structure-learning from data. We, then, go on to propose a novel heuristic designed to reduce the algorithmic complexity without engendering any loss of information. Ultimately, our conceived approach will be tested on a car diagnosis as well as on a Lymphography diagnosis data-bases, while our achieved results would be discussed, along with an exposition of our conducted work's interests as a closing step to this work. © 2012 Springer-Verlag.

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11页 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：