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

109 篇 会议
2 册 图书

馆藏范围

111 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

104 篇 工学
- 102 篇 计算机科学与技术...
- 11 篇 软件工程
- 3 篇 控制科学与工程
- 2 篇 力学（可授工学、理...
- 2 篇 材料科学与工程（可...
- 2 篇 化学工程与技术
- 2 篇 生物工程
- 2 篇 安全科学与工程
- 1 篇 机械工程
- 1 篇 冶金工程
- 1 篇 动力工程及工程热...
- 1 篇 电气工程
- 1 篇 信息与通信工程
- 1 篇 建筑学
- 1 篇 水利工程
- 1 篇 航空宇航科学与技...
- 1 篇 农业工程
9 篇 理学
- 6 篇 数学
- 3 篇 生物学
- 2 篇 统计学（可授理学、...
- 1 篇 物理学
- 1 篇 化学
- 1 篇 大气科学
- 1 篇 海洋科学
6 篇 管理学
- 4 篇 图书情报与档案管...
- 2 篇 管理科学与工程(可...
2 篇 教育学
- 2 篇 教育学
1 篇 经济学
- 1 篇 应用经济学
1 篇 法学
- 1 篇 社会学
1 篇 农学
- 1 篇 作物学
1 篇 医学

主题

19 篇 deep learning
19 篇 machine learning
5 篇 data mining
4 篇 classification
4 篇 data augmentatio...
3 篇 ensemble learnin...
3 篇 industry 4.0
3 篇 telecommunicatio...
3 篇 generative adver...
3 篇 big data
3 篇 optimization
3 篇 imbalanced data
3 篇 artificial intel...
3 篇 computer vision
3 篇 convolutional ne...
3 篇 convolutional ne...
2 篇 data generation
2 篇 pitch angle
2 篇 reinforcement le...
2 篇 clustering

机构

6 篇 univ porto fac e...
4 篇 univ minho algor...
4 篇 univ minho campu...
3 篇 univ minho ctr a...
3 篇 liaad inesc tec ...
3 篇 yonsei univ dept...
3 篇 artificial intel...
2 篇 univ essex sch c...
2 篇 univ politecn ma...
2 篇 univ sao paulo i...
2 篇 nos comunicacoes...
2 篇 university of mi...
2 篇 univ complutense...
2 篇 university of ma...
2 篇 univ twente ensc...
2 篇 bosch car multim...
2 篇 faculty of scien...
2 篇 univ complutense...
2 篇 univ fed pernamb...
2 篇 rey juan carlos ...

作者

6 篇 santos matilde
5 篇 machado jose
4 篇 novais paulo
4 篇 naranjo valery
4 篇 cho sung-bae
3 篇 ferreira diana
3 篇 horvath tomas
3 篇 mendes-moreira j...
3 篇 lori nicolas
3 篇 bu seok-jun
3 篇 colomer adrian
3 篇 lancho carmen
3 篇 cardoso henrique...
3 篇 de carvalho andr...
3 篇 camacho david
3 篇 pereira carlos
2 篇 garcia kemilly d...
2 篇 rubio thiago r. ...
2 篇 fonseca joaquim
2 篇 cruz jose aleixo

语言

111 篇 英文

检索条件"任意字段=21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020"

共 111 条记录，以下是91-100 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：

Sequence Mining for Automatic Generation of Software Tests from GUI Event Traces 21st

Sequence Mining for Automatic Generation of Software Tests f...

引用

21st international conference on intelligent data engineering and automated learning

作者： Oliveira, Alberto Freitas, Ricardo Jorge, Alipio Amorim, Vitor Moniz, Nuno Paiva, Ana C. R. Azevedo, Paulo J. Univ Porto FCUP LIAAD INESC TEC Porto Portugal RandTech Comp R&D Porto Portugal Univ Porto FEUP INESC TEC Porto Portugal Univ Minho INESC TEC Braga Portugal

ISBN: (纸本)9783030623647;9783030623654

In today's software industry, systems are constantly changing. To maintain their quality and to prevent failures at controlled costs is a challenge. One way to foster quality is through thorough and systematic testing. therefore, the definition of adequate tests is crucial for saving time, cost and effort. this paper presents a framework that generates software test cases automatically based on user interaction data. We propose a data-driven software test generation solution that combines the use of frequent sequence mining and Markov chain modeling. We assess the quality of the generated test cases by empirically evaluating their coverage with respect to observed user interactions and code. We also measure the plausibility of the distribution of the events in the generated test sets using the Kullback-Leibler divergence.

关键词： Software testing Frequent pattern mining Markov chains data mining

来源：评论

学校读者我要写书评

暂无评论

Anticipating Maintenance in Telecom Installation Processes 21st

Anticipating Maintenance in Telecom Installation Processes

引用

21st international conference on intelligent data engineering and automated learning

作者： Costa, Diana Pereira, Carlos Peixoto, Hugo Machado, Jose Univ Minho Campus Gualtar P-4710 Braga Portugal NOS Senhora Da Hora Portugal Univ Minho Algoritmi Ctr Campus Gualtar P-4710 Braga Portugal

ISBN: (纸本)9783030623647;9783030623654

Improving customer experience is crucial in any industry, especially in telecommunications, where competition is a constant factor. Today, all telecommunications companies rely on the massive amount of data generated daily to get to know the customer or study their behavior and thus create new effective strategies for their business. Within the most varied user experiences, the process of installing new services can be an event that raises doubts about their operation, degrade the user experience, or, in extreme cases, lead to maintenance interventions. therefore, the use of advanced predictive models that can predict such occurrences become vital. With this, the company can anticipate the cases that will be problematic and reduce the number of negative experiences. the main objective of this work is to create a predictive model that, through all the available data history, can predict which customers will contact the customer service with problems derived from the installation process and have a following maintenance intervention. After analyzing an unbalanced dataset with approximately 560K entries from a Portuguese telecommunications company, and resorting to the CRISPDM methodology for modeling, the best results were found with Light-GBM which obtained an AUPRC of 0.11 and AUROC of 0.62. the best trade-off between precision and recall was found with a threshold model of 0.43 in order to maximize recall while still avoiding a large number of false negatives.

关键词： Customer data mining Installation Machine learning Predict Service Telecommunications

来源：评论

学校读者我要写书评

暂无评论

A learning-to-rank algorithm for constructing defect prediction models

A learning-to-rank algorithm for constructing defect predict...

引用

13th international conference on intelligent data engineering and automated learning, ideal 2012

作者： Yang, Xiaoxing Tang, Ke Yao, Xin NICAL School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China CERCIA School of Computer Science University of Birmingham United Kingdom

ISBN: (纸本)9783642326387

this paper applies the learning-to-rank approach to software defect prediction. Ranking software modules in order of defect-proneness is important to ensure that testing resources are allocated efficiently. However, prediction models that are optimized for predicting explicitly the number of defects often fail to correctly predict rankings based on those defect numbers. We show in this paper that the model construction methods, which include the ranking performance measure in the objective function, perform better in predicting defect-proneness rankings of multiple modules. We present the experimental results, in which our method is compared against three other methods from the literature, using five publicly available data sets. © 2012 Springer-Verlag.

关键词： Software testing

来源：评论

学校读者我要写书评

暂无评论

An intelligent Procedure for the Methodology of Energy Consumption in Industrial Environments 21st

An Intelligent Procedure for the Methodology of Energy Consu...

引用

21st international conference on intelligent data engineering and automated learning

作者： Mendia, Izaskun Gil-Lopez, Sergio Del Ser, Javier Grau, Inaki Lejarazu, Adelaida Maqueda, Erik Perea, Eugenio TECNALIA Basque Res & Technol Alliance BRTA Mikeletegi Pasealekua 2 Donostia San Sebastian 20009 Spain Univ Basque Country UPV EHU Bilbao 48013 Spain Gestamp Madrid 28014 Spain

ISBN: (纸本)9783030623647;9783030623654

the concern of the industrial sector about the increase of energy costs has stimulated the development of new strategies for the effective management of energy consumption in industrial setups. Along with this growth, the irruption and continuous development of digital technologies have generated increasingly complex industrial ecosystems. these ecosystems are supported by a large number of variables and procedures for the operation and control of industrial processes and assets. this heterogeneous technological scenario has made industries difficult to manage by traditional means. In this context, the disruptive potential of cyber physical systems is beginning to be considered in the automation and improvement of industrial services. Particularly, intelligent data-driven approaches relying on the combination of Energy Management Systems (EMS), Manufacturing Execution Systems (MES), Internet of things (IoT) and data Analytics provide the intelligence needed to optimally operate these complex industrial environments. the work presented in this manuscript contributes to the definition of the aforementioned intelligent data-driven approaches, defining a systematic, intelligent procedure for the energy efficiency diagnosis and improvement of industrial plants. this data-based diagnostic procedure hinges on the analysis of data collected from industrial plants, aimed at minimizing energy costs through the continuous assessment of the production-consumption ratio of the plant (i.e. energy per piece or kg produced). the proposed methodology aims to support managers and energy-efficiency technicians to minimize the plant's energy consumption without affecting the production and therefore, increase its competitiveness. the data used in the design of this methodology are real data from a company dedicated to the design and manufacture of automotive components and one of the main manufacturers in the automotive sector worldwide. the present methodology is under the pending pat

关键词： Energy efficiency Smart manufacturing intelligent systems Industry 4.0 Big data Cyber physical systems

来源：评论

学校读者我要写书评

暂无评论

Review of Trends in Automatic Human Activity Recognition in Vehicle Based in Synthetic data 21st

Review of Trends in Automatic Human Activity Recognition in ...

引用

21st international conference on intelligent data engineering and automated learning

作者： Coimbra, Ana Neto, Cristiana Ferreira, Diana Duarte, Julio Oliveira, Daniela Hak, Francini Goncalves, Filipe Fonseca, Joaquim Lori, Nicolas Abelha, Antonio Machado, Jose Univ Minho Ctr Algoritmi P-4710057 Braga Portugal Bosch Car Multimedia P-4705820 Braga Portugal

ISBN: (纸本)9783030623647;9783030623654

Driverless vehicles are more and more becoming a reality. However, people still have some concerns in using them, the main concern is fear, hence the importance of creating a surveillance system inside those vehicles. For the detection and classification of human movements to be possible it is necessary to train the system with data representative enough for all kinds of possibilities. Although the production of large quantities of data becomes an expensive process and adds the problem of data protection, the use of synthetic data once they are artificially generated allows lower costs and eliminates the problem of data protection. A bibliographic study was carried out in this paper with articles from 2017 or later on the use of synthetic data. In these studies, it is noted that synthetic data is widely used with good results. As far as image capture is concerned, they show that 3D cameras have better results, but they are more expensive, so 2D cameras are more often used with later conversion to 3D images. the stitched puppet (SP) model is capable of adapting to the most difficult poses having obtained good results in its application in the FAUST dataset.

关键词： Autonomous car Multisensory fusion Audio-visual synthetic data

来源：评论

学校读者我要写书评

暂无评论

Extraction by example: Induction of structural rules for the analysis of molecular sequence data from heterogeneous sources

Extraction by example: Induction of structural rules for the...

引用

6th international conference on intelligent data engineering and automated learning - ideal 2005

作者： Miotto, Olivo Tan, Tin Wee Brusic, Vladimir Institute of Systems Science National University of Singapore 25 Heng Mui Keng Terrace Singapore 119615 Singapore Department of Biochemistry Faculty of Medicine National University of Singapore 10 Medical Drive Singapore 117597 Singapore Institute for Infocomm Research Singapore 21 Heng Mui Keng Terrace Singapore 119613 Singapore

Biological research requires information from multiple data sources that use a variety of database-specific formats. Manual gathering of information is time consuming and error-prone, making automated data aggregation a compelling option for large studies. We describe a method for extracting information from diverse sources that involves structural rules specified by example. We developed a system for aggregation of biological knowledge (ABK) and used it to conduct an epidemiological study of dengue virus (DENV) sequences. Additional information on geographical origin and isolation date is critical for understanding evolutionary relationships, but this data is inconsistently structured in database entries. Using three public databases, we found that structural rules can be used successfully even when applied on inconsistently structured data that is distributed across multiple fields. High reusability, combined with the ability to integrate analysis tools, make this method suitable for a wide variety of large-scale studies involving viral sequences. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Information analysis

来源：评论

学校读者我要写书评

暂无评论

the Future with Advanced Analytics: A Sequential Analysis of the Disruptive Technology’s Scope 20th

The Future with Advanced Analytics: A Sequential Analysis of...

引用

20th international conference on Hybrid intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired Computing, NaBIC 2020

作者： Varsha, R. Nair, Siddharth M. Tyagi, Amit Kumar Aswathy, S.U. RadhaKrishnan, R. School of Computer Science and Engineering Vellore Institute of Technology Chennai Campus ChennaiTamil Nadu600127 India Center for Advanced Data Science Vellore Institute of Technology ChennaiTamilnadu600127 India School of Computer Science and Engineering Vellore Institute of Technology ChennaiTamilnadu600127 India Department of Computer Science Jyothi Engineering College ThrissurKerala India Department of Civil Engineering Mangakam College of Engineering Kottayam India

ISBN: (纸本)9783030730499

Today every application like e-healthcare, agriculture, etc., is connected through smart devices to reduce workforce and enhance productivity. Many applications like defences, banking an utilities, media and entertainment, transportation, banking, retail, agriculture, education, manufacturing, etc., are using smart devices in their working-structure to improved growth of a business/production. these applications are generating a lot of data, which called as "big data" and this data is increasing at a huge rate. For example, most of the data (90%) is generated in last decade only. Together this, we required modern tools to analyses this data for generating useful results. But in near future, this analytics process may shift towards automation. How these automated analytics by deep learning (by robots/machines) will change future forever. Also, with this automated/advanced analytics process we need to provide a disruptive environment which is more towards to protecting nature. this article provide detail explanation regarding "how machines can be useful in learning process through its automate learning process" and "how machine/Artificial Intelligence (AI) can be useful in detecting vulnerabilities/intrusion without much human interaction instantly" and so on. In 21st century, most of tasks will be completed by machines or artificial intelligences. this work discusses several useful terms, scenarios (with many examples in several applications), tools, open issues with opportunities towards automated analytics, i.e., with discussing that "How AI will change near future". © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

learning Inter-Lingual Document Representations via Concept Compression 22nd

Learning Inter-Lingual Document Representations via Concept ...

引用

22nd international conference on intelligent data engineering and automated learning, ideal 2021

作者： Lenz, Marc Tashu, Tsegaye Misikir Horváth, Tomáš Faculty of Informatics Department of Data Science and Engineering Telekom Innovation Laboratories ELTE - Eötvös Loránd University Pázmány Péter Sétány Budapest1117 Hungary College of Informatics Wollo University Kombolcha Institute of Technology Kombolcha208 Ethiopia Faculty of Science Institute of Computer Science Pavol Jozef Šafárik University Jesenná 5 Košice040 01 Slovakia

ISBN: (纸本)9783030916077

In this work, we proposed a novel approach to derive inter-lingual document representations. the introduced methods aim to enhance the quality of content-based Multilingual Document Recommendation and information retrieval Systems. the main idea centers around creating inter-lingual representations by using mappings to align monolingual representation spaces. According to the experimental results carried out on JRC-Acquis and EU bookshop multilingual corpora, the proposed concept compression approach has outperformed the traditional cross-lingual retrieval and recommendations methods. © 2021, Springer Nature Switzerland AG.

关键词： Information retrieval systems

来源：评论

学校读者我要写书评

暂无评论

Hebbian learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks 24th

Hebbian Learning-Guided Random Walks for Enhanced Community ...

引用

24th international conference on intelligent data engineering and automated learning, ideal 2023

作者： Sotero, Roberto C. Sanchez-Bornot, Jose M. Department of Radiology and Hotchkiss Brain Institute University of Calgary CalgaryAB Canada Intelligent Systems Research Centre Ulster University Derry Londonderry United Kingdom

ISBN: (纸本)9783031482311

Community detection in complex signed networks is a significant challenge, traditionally addressed using the Louvain method directly applied to the correlation matrix. this study introduces a two-tier approach that integrates a Hebbian learning rule within an adaptive signed random walk (ASRW) framework, then applies the Louvain method to the final weight matrix. this approach refines the network analysis process, providing a new tool for exploring community structure. Tested extensively on synthetic signed networks with defined community structures, our methodology consistently outperformed the traditional Louvain approach, particularly when communities were less clearly demarcated. Further application to resting-state functional MRI data from the ABIDE Preprocessed Initiative highlighted functional connectivity differences between neurotypical individuals and those diagnosed with Autism Spectrum Disorder (ASD). Our approach found key areas of significant difference, including several cerebellum regions, consistent with existing ASD literature. Our findings underscore the potential of the proposed technique to advance community detection in correlation-based networks. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Population dynamics

来源：评论

学校读者我要写书评

暂无评论

Linear Concept Approximation for Multilingual Document Recommendation 22nd

Linear Concept Approximation for Multilingual Document Recom...

引用

22nd international conference on intelligent data engineering and automated learning, ideal 2021

作者： Salamon, Vilmos Tibor Tashu, Tsegaye Misikir Horváth, Tomáš ELTE - Eötvös Loránd University Faculty of Informatics Department of Data Science and Engineering Telekom Innovation Laboratories Pázmány Péter sétány 1/C Budapest1117 Hungary Kombolcha Institute of Technology College of Informatics Wollo University Kombolcha208 Ethiopia Faculty of Science Institute of Computer Science Pavol Jozef Šafárik University Jesenná 5 Košice040 01 Slovakia

ISBN: (纸本)9783030916077

In this paper, we proposed Linear Concept Approximation, a novel multilingual document representation approach for the task of multilingual document representation and recommendation. the main idea is in creating representations by using mappings to align monolingual representation spaces using linear concept approximation, that in turn will enhance the quality of content-based Multilingual Document Recommendation Systems. the experimental results on JRC-Acquis have shown that our proposed approach outperformed traditional methods on the task of multilingual document recommendation. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

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12页 << < 3 4 5 6 7 8 9 10 11 12 > >>

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：