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

3,117 篇 会议
142 册 图书
22 篇 期刊文献

馆藏范围

3,280 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,140 篇 工学
- 1,954 篇 计算机科学与技术...
- 1,096 篇 软件工程
- 404 篇 信息与通信工程
- 285 篇 电气工程
- 267 篇 生物工程
- 217 篇 控制科学与工程
- 172 篇 生物医学工程（可授...
- 79 篇 化学工程与技术
- 73 篇 光学工程
- 72 篇 机械工程
- 67 篇 仪器科学与技术
- 65 篇 电子科学与技术（可...
- 62 篇 安全科学与工程
- 55 篇 动力工程及工程热...
- 54 篇 网络空间安全
776 篇 理学
- 429 篇 数学
- 295 篇 生物学
- 151 篇 统计学（可授理学、...
- 148 篇 物理学
- 127 篇 系统科学
- 89 篇 化学
505 篇 管理学
- 306 篇 图书情报与档案管...
- 231 篇 管理科学与工程(可...
- 95 篇 工商管理
218 篇 医学
- 193 篇 临床医学
- 125 篇 基础医学(可授医学...
- 87 篇 药学(可授医学、理...
- 55 篇 公共卫生与预防医...
72 篇 法学
- 70 篇 社会学
51 篇 教育学
- 47 篇 教育学
35 篇 经济学
31 篇 农学
6 篇 艺术学
4 篇 军事学
1 篇 文学

主题

568 篇 data mining
543 篇 machine learning
242 篇 pattern recognit...
195 篇 deep learning
174 篇 feature extracti...
154 篇 artificial intel...
153 篇 support vector m...
113 篇 accuracy
113 篇 machine learning...
110 篇 training
93 篇 data models
80 篇 neural networks
78 篇 data mining and ...
65 篇 classification
62 篇 sentiment analys...
61 篇 classification a...
59 篇 big data
57 篇 predictive model...
50 篇 face recognition
48 篇 prediction algor...

机构

7 篇 maharishi school...
6 篇 guangdong univer...
5 篇 galgotias univer...
5 篇 centre of interd...
5 篇 pune
5 篇 chitkara univers...
5 篇 king fahd univer...
5 篇 uttaranchal univ...
5 篇 uttaranchal inst...
5 篇 institute of aut...
4 篇 indian institute...
4 篇 shanghai jiao to...
4 篇 chitkara univers...
4 篇 school of inform...
4 篇 indian statistic...
4 篇 south china univ...
4 篇 zhejiang univers...
4 篇 maharishi school...
4 篇 department of cs...
4 篇 university of ca...

作者

9 篇 de-shuang huang
7 篇 coenen frans
7 篇 venkatesh svetha
7 篇 petra perner
7 篇 tianrui li
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 jacek m. zurada
6 篇 krasotkina olga
6 篇 lotfi a. zadeh
6 篇 mottl vadim
6 篇 leszek rutkowski
5 篇 vitoantonio bevi...
5 篇 sankar k. pal
4 篇 waiyamai kitsana
4 篇 sozo inoue
4 篇 sergei o. kuznet...
4 篇 duoqian miao
4 篇 shengli xie
4 篇 hepu deng

语言

2,835 篇 英文
436 篇 其他
45 篇 中文
1 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3281 条记录，以下是2351-2360 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：

Sentiment Analysis for Government: An Optimized Approach 11th

Sentiment Analysis for Government: An Optimized Approach

引用

11th international conference on machine learning and data mining (MLDM)

作者： Corallo, Angelo Fortunato, Laura Matera, Marco Alessi, Marco Camillo, Alessio Chetta, Valentina Giangreco, Enza Storelli, Davide Univ Salento Dipartimento Ingn Innovaz Lecce Italy Engn Ingn Informat SPA R&D Dept Palermo Italy Engn Ingn Informat SPA R&D Dept Lecce Italy

ISBN: (纸本)9783319210247;9783319210230

This paper describes a Sentiment Analysis (SA) method to analyze tweets polarity and to enable government to describe quantitatively the opinion of active users on social networks with respect to the topics of interest to the Public Administration. We propose an optimized approach employing a document-level and a dataset-level supervised machine learning classifier to provide accurate results in both individual and aggregated sentiment classification. The aim of this work is also to identify the types of features that allow to obtain the most accurate sentiment classification for a dataset of Italian tweets in the context of a Public Administration event, also taking into account the size of the training set. This work uses a dataset of 1,700 Italian tweets relating to the public event of "Lecce 2019 - European Capital of Culture".

关键词： Sentiment analysis machine learning Public administration

来源：评论

学校读者我要写书评

暂无评论

Mapping Evaluation for Semantic Browsing

Mapping Evaluation for Semantic Browsing

引用

3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Osinska, Veslava Jozwik, Adam Osinski, Grzegorz Nicolaus Copernicus Univ Inst Informat Sci & Book Studies Ul Bojarskiego 1 PL-87100 Torun Poland Polish Acad Sci Inst Biocybernet & Biomed Engn Warsaw Poland Coll Social & Media Culture Inst Comp Sci PL-87100 Torun Poland

ISBN: (纸本)9788360810668

The paper contributes to the problem solving in semantic browsing and analysis of scientific articles. With reference to presented visual interface, four - the most popular methods of mapping including own approach - MDS with spherical topology, have been compared. For a comparison quantitative measures were applied which allowed to select the most appropriate mapping way with an accurate reflection of the dynamics of data. For the quantitative analysis the authors used machine learning and pattern recognition algorithms and described: clusterization degree, fractal dimension and lacunarity. Local density differences, clusterization, homogeneity, and gappiness were measured to show the most acceptable layout for an analysis, perception and exploration processes. Visual interface for analysis how computer science evolved through the two last decades is presented on website. Results of both quantitative and qualitative analysis have revealed good convergence.

关键词： Web sites learning (artificial intelligence) problem solving MDS Website local density differences machine learning pattern recognition algorithms semantic browsing visual interface Computer science data visualization Fractals Layout Semantics Training Visualization

来源：评论

学校读者我要写书评

暂无评论

A New Automatic Quality Control System for Fiber Ring Production 15th

A New Automatic Quality Control System for Fiber Ring Produc...

引用

15th international conference on Man-machine-Environment System Engineering (MMESE)

作者： Li, Xinfeng Liu, Haoting Hangtian Dianzi 1 Fengying East Rd Beijing 100094 Peoples R China

ISBN: (纸本)9783662482247;9783662482230

Fiber optical gyro (FOG) as one of the most important component in Fiber inertial measure unit (FIMU), the production quality of which will affect the accuracy of FOG and FIMU;through decade years improvement in craftwork design, the main target has shifted to quality control promotion during production. This paper has proposed a new methodology for automatic production quality control;the method uses the computer vision technology to apply a system which can distinguish real-time fiber ring production images, applying pattern recognition of data mining technology for understanding of the type of fault production image. Pre-processing of computer vision has treatment to distil the image from real-time noised image for feature achievement, upon the qualified conducted result;a fast pattern recognition method support vector regression (SVR) has fast convergence which has utilized delightful result.

关键词： FOG FIMU Fiber ring Median filter pattern recognition Support vector regression (SVR)

来源：评论

学校读者我要写书评

暂无评论

learning Instead of Markers: Flexible recognition of Mobile Devices on Interactive Surfaces 3rd

Learning Instead of Markers: Flexible Recognition of Mobile ...

引用

3rd international conference on Distributed, Ambient, and Pervasive Interactions (DAPI) held as Part of 17th international conference on Human-Computer Interaction (HCI)

作者： Mock, Philipp Edelmann, Joerg Rosenstiel, Wolfgang Univ Tubingen D-72076 Tubingen Germany Knowledge Media Res Ctr D-72076 Tubingen Germany

ISBN: (纸本)9783319208046;9783319208039

We propose an approach for recognition of mobile devices on interactive surfaces that do not support optical markers. Our system only requires an axis aligned bounding box of the object placed on the touchscreen in combination with position data from the mobile devices integrated inertia measurement unit (IMU). We put special emphasis on maximum flexibility in terms of compatibility with varying multi-touch sensor techniques and different kinds of mobile devices. A new device can be added to the system with a short training phase, during which the device is moved across the interactive surface. A device model is automatically created from the recorded data using support vector machines. Different devices of the same size are identified by analyzing their IMU data streams for transitions into a horizontally resting state. The system has been tested in a museum environment.

关键词： Human computer interaction Tabletop interaction Markerless object tracking machine learning

来源：评论

学校读者我要写书评

暂无评论

Optimizing the data-Process Relationship for Fast mining of Frequent Itemsets in MapReduce 11th

Optimizing the Data-Process Relationship for Fast Mining of ...

引用

11th international conference on machine learning and data mining (MLDM)

作者： Salah, Saber Akbarinia, Reza Masseglia, Florent Univ Montpellier Inria F-34059 Montpellier France Univ Montpellier LIRMM Zenith Team F-34059 Montpellier France

ISBN: (纸本)9783319210247;9783319210230

Despite crucial recent advances, the problem of frequent itemset mining is still facing major challenges. This is particularly the case when: (i) the mining process must be massively distributed and;(ii) the minimum support (MinSup) is very low. In this paper, we study the effectiveness and leverage of specific data placement strategies for improving parallel frequent itemset mining (PFIM) performance in MapReduce, a highly distributed computation framework. By offering a clever data placement and an optimal organization of the extraction algorithms, we show that the itemset discovery effectiveness does not only depend on the deployed algorithms. We propose ODPR (Optimal data-Process Relationship), a solution for fast mining of frequent itemsets in MapReduce. Our method allows discovering itemsets from massive datasets, where standard solutions from the literature do not scale. Indeed, in a massively distributed environment, the arrangement of both the data and the different processes can make the global job either completely inoperative or very effective. Our proposal has been evaluated using real-world data sets and the results illustrate a significant scale-up obtained with very low MinSup, which confirms the effectiveness of our approach.

关键词： MapReduce

来源：评论

学校读者我要写书评

暂无评论

mining Educational data to Predict Students' Academic Performance 11th

Mining Educational Data to Predict Students' Academic Perfor...

引用

11th international conference on machine learning and data mining (MLDM)

作者： Al-Saleem, Mona Al-Kathiry, Norah Al-Osimi, Sara Badr, Ghada King Saud Univ Riyadh Saudi Arabia IRI City Sci Res & Technol Applicat Alexandria Egypt Qassim Univ Buraydah Saudi Arabia

ISBN: (纸本)9783319210247;9783319210230

data mining is the process of extracting useful information from a huge amount of data. One of the most common applications of data mining is the use of different algorithms and tools to estimate future events based on previous experiences. In this context, many researchers have been using data mining techniques to support and solve challenges in higher education. There are many challenges facing this level of education, one of which is helping students to choose the right course to improve their success rate. An early prediction of students' grades may help to solve this problem and improve students' performance, selection of courses, success rate and retention. In this paper we use different classification techniques in order to build a performance prediction model, which is based on previous students' academic records. The model can be easily integrated into a recommender system that can help students in their course selection, based on their and other graduated students' grades. Our model uses two of the most recognised decision tree classification algorithms: ID3 and J48. The advantages of such a system have been presented along with a comparison in performance between the two algorithms.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Incremental learning and Novelty Detection of Gestures in a Multi-Class System 3

Incremental Learning and Novelty Detection of Gestures in a ...

引用

3rd international conference on Artificial Intelligence, Modelling and Simulation (AIMS)

作者： Al-Behadili, Husam Grumpe, Arne Woehler, Christian Univ Mustansiriyah Engn Coll Dept Elect Baghdad Iraq Univ Mustansiriyah Engn Coll Dept Elect Baghdad Iraq TU Dortmund Image Anal Grp Dortmund Germany

ISBN: (纸本)9781467386753

The difficulties of data streams, i.e. infinite length, the occurrence of concept-drift and the possible emergence of novel classes, are topics of high relevance in the field of recognition systems. To overcome all of these problems, the system should be updated continuously with new data while the amount of processing time should be kept small. We propose an incremental Parzen window kernel density estimator ( IncPKDE) which addresses the problems of data streaming using a model that is insensitive to the training set size and has the ability to detect novelties within multi-class recognition systems. The results show that the IncPKDE approach has superior properties especially regarding processing time and that it is robust to wrongly labelled samples if used in a semi-supervised learning scenario.

关键词： parzen window novelty detection incremental learning semi-supervised learning

来源：评论

学校读者我要写书评

暂无评论

9th international conference on Practical Applications of Computational Biology and Bioinformatics 1

引用

丛书名： Advances in Intelligent Systems and Computing 375

2015年

作者： Ross Overbeek, Miguel P. Rocha, Florentino Fdez-Riverola, Juan F. De Paz (eds.)

ISBN: (数字)9783319197753;9783319197760

ISBN: (纸本)9783319197753;9783319197760

This proceedings presents recent practical applications of Computational Biology and Bioinformatics. It contains the proceedings of the 9th international conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The international conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as databases, Statistics, data mining, machine learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Patient-Specific Modeling of Medical data 11th

Patient-Specific Modeling of Medical Data

引用

11th international conference on machine learning and data mining (MLDM)

作者： Sousa Ribeirol, Guilherme Alberto Muniz de Oliveiral, Alexandre Cesar Ferreira, Antonio Luiz S. Visweswaran, Shyam Cooper, Gregory F. Univ Fed Maranhao Dept Informat BR-1966 Sao Luis MA Brazil Univ Pittsburgh Dept Biomed Informat Pittsburgh PA 15206 USA

ISBN: (纸本)9783319210247;9783319210230

Patient-specific models are instance-based learn algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the standard entropy-based method, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

关键词： Classification problems Approach instance-based Area under the roc curve

来源：评论

学校读者我要写书评

暂无评论

learning Heuristics to Reduce the Overestimation of Bipartite Graph Edit Distance Approximation 11th

Learning Heuristics to Reduce the Overestimation of Bipartit...

引用

11th international conference on machine learning and data mining (MLDM)

作者： Ferrer, Miquel Serratosa, Francesc Riesen, Kaspar Univ Appl Sci & Arts Northwestern Switzerland Inst Informat Syst CH-4600 Olten Switzerland Univ Rovira & Virgili Dept Engn Informat & Matemat Tarragoa 43007 Spain

ISBN: (纸本)9783319210247;9783319210230

In data mining systems, which operate on complex data with structural relationships, graphs are often used to represent the basic objects under study. Yet, the high representational power of graphs is also accompanied by an increased complexity of the associated algorithms. Exact graph similarity or distance, for instance, can be computed in exponential time only. Recently, an algorithmic framework that allows graph dissimilarity computation in cubic time with respect to the number of nodes has been presented. This fast computation is at the expense, however, of generally overestimating the true distance. The present paper introduces six different post-processing algorithms that can be integrated in this suboptimal graph distance framework. These novel extensions aim at improving the overall distance quality while keeping the low computation time of the approximation. An experimental evaluation clearly shows that the proposed heuristics substantially reduce the overestimation in the existing approximation framework while the computation time remains remarkably low.

关键词： data mining

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329页 << < 232 233 234 235 236 237 238 239 240 241 > >>

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：