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

3,226 篇 会议
74 篇 期刊文献
54 册 图书

馆藏范围

3,354 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,176 篇 工学
- 1,933 篇 计算机科学与技术...
- 702 篇 软件工程
- 418 篇 电气工程
- 333 篇 信息与通信工程
- 181 篇 控制科学与工程
- 79 篇 仪器科学与技术
- 73 篇 生物医学工程（可授...
- 64 篇 生物工程
- 48 篇 机械工程
- 46 篇 航空宇航科学与技...
- 35 篇 电子科学与技术（可...
- 33 篇 化学工程与技术
- 30 篇 光学工程
- 30 篇 网络空间安全
- 28 篇 动力工程及工程热...
- 27 篇 交通运输工程
423 篇 管理学
- 285 篇 管理科学与工程(可...
- 139 篇 图书情报与档案管...
- 74 篇 工商管理
399 篇 理学
- 199 篇 数学
- 116 篇 物理学
- 87 篇 生物学
- 68 篇 统计学（可授理学、...
- 50 篇 系统科学
- 45 篇 化学
- 42 篇 地球物理学
77 篇 医学
- 63 篇 基础医学(可授医学...
- 57 篇 临床医学
- 36 篇 药学(可授医学、理...
56 篇 法学
- 51 篇 社会学
28 篇 教育学
26 篇 经济学
12 篇 农学
4 篇 文学
3 篇 艺术学
1 篇 军事学

主题

1,150 篇 data mining
336 篇 big data
212 篇 cloud computing
150 篇 data models
123 篇 feature extracti...
118 篇 algorithm design...
95 篇 databases
80 篇 computational mo...
74 篇 clustering algor...
72 篇 training
71 篇 semantics
71 篇 machine learning
65 篇 conferences
63 篇 clustering
63 篇 support vector m...
63 篇 servers
61 篇 classification a...
56 篇 classification
56 篇 sentiment analys...
52 篇 predictive model...

机构

41 篇 infn sezione di ...
41 篇 infn sezione di ...
41 篇 universidade de ...
41 篇 universidad de m...
41 篇 universidade de ...
41 篇 torino
41 篇 palacky universi...
41 篇 palermo
41 篇 infn sezione di ...
41 篇 institute for as...
41 篇 infn sezione di ...
41 篇 rwth aachen univ...
41 篇 institut für pro...
41 篇 centro federal d...
41 篇 university of ad...
41 篇 charles universi...
41 篇 universität hamb...
40 篇 infn sezione di ...
40 篇 sorbonne univers...
40 篇 cnrs in2p3 ijcla...

作者

42 篇 aloisio r.
41 篇 almeida cheminan...
41 篇 aglietta m.
41 篇 anastasi g.a.
41 篇 buscemi m.
41 篇 catalani f.
41 篇 de souza v.
40 篇 bismark k.
40 篇 fazzini n.
40 篇 avila g.
40 篇 emam m.
40 篇 de mitri i.
40 篇 covault c.e.
40 篇 deligny o.
40 篇 condorelli a.
40 篇 cataldi g.
40 篇 cobos cerutti a....
40 篇 brack j.
40 篇 conte m.
40 篇 di matteo a.

语言

3,304 篇 英文
28 篇 其他
18 篇 中文
2 篇 葡萄牙文
2 篇 俄文
1 篇 德文

检索条件"任意字段=2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016"

共 3354 条记录，以下是291-300 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：

A Distinct Cyberattack: Phishing

A Distinct Cyberattack: Phishing

引用

international conference on advanced computing and Intelligent Engineering (ICACIE)

作者： Jayanthi, G. Prisilla Geethanjali Coll Engn & Technol Dept Comp Sci Engn Hyderabad Telangana India

ISBN: (纸本)9789811068720;9789811068713

The cyberattack happens to be a nation concern-as the target can hold the confidential matter of military or a commercial business with the intellectual assets and viable secrets that pave the way to challenge. The majorities of the professionals are aware of the cyberattacks on the data center space but are helpless and have a severe impact on the two domains. The prime domain, information technology which refers to the information processing-servers, storage arrays. The other one is about the physical infrastructure that controls the first domain. The cyberattacks on the network can be mitigated through the educative programs for the employees and training the staffs with the certain basic security policies. Introducing the preventive techniques can defend the sensitive data from the hackers.

关键词： Cyberattacks Cyber criminals Phishing Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Impacts of Big data on data mining Research An Empirical Study of Chinese Journals 18

Impacts of Big Data on Data Mining Research An Empirical Stu...

引用

3rd international conference on Crowd Science and Engineering (ICCSE)

作者： Huang, Yue Beijing Language & Culture Univ Sch Informat Sci Beijing Peoples R China

ISBN: (纸本)9781450365871

With the advent of big data, data mining theories and methods face new challenges. This paper tries to find the impacts of big data on data mining research through 23377 data mining-related papers published in Chinese academic journals during 1996-2016. By utilization of various methods of bibliometrics, this study conducts three different levels of analysis to gradually dig deeper into the contents of literature. For the macro-level, paper amount analysis results show that big data-related research began in 2012 and has brought new growth to data mining area. For the meso-level, journal distribution analysis results indicate that many other disciplines, such as arts and agriculture science, began to apply data mining techniques with the wide spread of big data. For the micro-level, co-word-based research topic clustering results imply that new topics emerged due to the easy access of big data, such as 'clouding computing' and 'teaching and learning analysis'.

关键词： Big data data mining Impact Bibliometrics

来源：评论

学校读者我要写书评

暂无评论

data Rate and Symbol Error Rate Analysis of Massive MIMO for 5G Applications

Data Rate and Symbol Error Rate Analysis of Massive MIMO for...

引用

international conference on advanced computing and Intelligent Engineering (ICACIE)

作者： Singh, Shipra Gupta, Sindhu Hak Rajawat, Asmita Amity Univ Uttar Pradesh Noida India

ISBN: (纸本)9789811068720;9789811068713

In this paper performance of the Massive MIMO is analyzed in terms of SER and SNR values. SER and high data rate is the current requirement for the 5G technology based on the observed result it may be concluded that Massive MIMO has lower SER values and this result is compared with the current MIMO technology. It is observed that SER values for Massive MIMO is comparatively very less than the MIMO system. Therefore, it will be beneficial to opt Massive MIMO concept for the next generation technology.

关键词： Massive MIMO Generations Bit error rate Symbol error rate

来源：评论

学校读者我要写书评

暂无评论

A Privacy-Preserving k-Means Clustering Algorithm using Secure Comparison Protocol and Density-based Center Point Selection 11

A Privacy-Preserving k-Means Clustering Algorithm using Secu...

引用

11th IEEE international conference on Cloud computing (CLOUD) Part of the IEEE World Congress on Services

作者： Kim, Hyeong-Jin Chang, Jae-Woo Chonbuk Natl Univ Dept Comp Sci & Engn Jeonju Si South Korea Chonbuk Natl Univ Dept Informat Technol & Engn Jeonju Si South Korea

ISBN: (纸本)9781538672358

Since studies on privacy-preserving database outsourcing have been spotlighted in a cloud computing, databases need to be encrypted before being outsourced to the cloud. Rao et al. proposed a k-Means clustering algorithm that supports the protection of sensitive data by using a paillier cryptosystemi[1]. However, the existing algorithm is inefficient due to bit-array based comparison. To solve this problem, we propose an efficient privacy-preserving k-Means clustering algorithm. First, we provide a new secure comparison protocol that performs the fast comparison of encrypted data. Second, we select center points by considering the distribution of the entire data. Finally, we show from our performance analysis that our clustering algorithm achieves about 300% better performance on average than the existing algorithm.

关键词： cloud computing secure multiparty computation data mining clustering algorithm paillier cryptosystem

来源：评论

学校读者我要写书评

暂无评论

Pybkgmodel - a background modelling toolbox for the CTA 38

Pybkgmodel - a background modelling toolbox for the CTA

引用

38th international Cosmic Ray conference, ICRC 2023

作者： Strzys, Marcel C. Abe, Shotaro de Bony de Lavergne, Mathieu Hütten, Moritz Mender, Simone Vovk, Ievgen Abe, K. Abe, S. Acharyya, A. Adam, R. Aguasca-Cabot, A. Agudo, I. Alfaro, J. Alvarez-Crespo, N. Alves Batista, R. Amans, J.-P. Amato, E. Ambrosino, F. Angüner, E.O. Antonelli, L.A. Aramo, C. Arcaro, C. Arrabito, L. Asano, K. Aschersleben, J. Ashkar, H. Augusto Stuani, L. Baack, D. Backes, M. Balazs, C. Balbo, M. Baquero Larriva, A. Barbosa Martins, V. de Almeida, U. Barres Barrio, J.A. Bastieri, D. Batista, P.I. Batkovic, I. Batzofin, R. Baxter, J. Beck, G. Becker Tjus, J. Beiske, L. Belardinelli, D. Benbow, W. Bernardini, E. Bernete Medrano, J. Bernlöhr, K. Berti, A. Beshley, V. Bhattacharjee, P. Bhattacharyya, S. Bi, B. Biederbeck, N. Biland, A. Bissaldi, E. Blanch, O. Blazek, J. Boisson, C. Bolmont, J. Bonnoli, G. Bordas, P. Bosnjak, Z. Bradascio, F. Braiding, C. Bronzini, E. Brose, R. Brown, A.M. Brun, F. Brunelli, G. Bulgarelli, A. Burelli, I. Burmistrov, L. Burton, M. Bylund, T. Calisse, P.G. Campoy-Ordaz, A. Cantlay, B.K. Capalbi, M. Caproni, A. Capuzzo-Dolcetta, R. Carlile, C. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.-S. Cascone, E. Cassol, F. Castrejon, N. Catalani, F. Cerasole, D. Cerruti, M. Chaty, S. Chen, A.W. Chernyakova, M. Chiavassa, A. Chudoba, J. Coimbra Araujo, C.H. Conforti, V. Conte, F. Contreras, J.L. Cossou, C. Costa, A. Costantini, H. Cristofari, P. Cuevas, O. Curtis-Ginsberg, Z. D'Amico, G. D'Ammando, F. Dadina, M. Dalchenko, M. David, L. Davids, I.D. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Caprio, V. De Cesare, G. de Gouveia Dal Pino, E.M. De Lotto, B. De Lucia, M. de Menezes, R. de Naurois, M. de Ona Wilhelmi, E. De Simone, N. de Souza, V. del Peral, L. del Valle, M.V. Delagnes, E. Delgado Giler, A.G. Delgado, C. Dell'aiera, M. Della Ceca, R. Della Valle, M. della Volpe, D. Depaoli, D. Dettlaff, A. Di Girolamo, T. Di Piano, A. Di Pierro, F. Di Tria, R. Di Venere, L. Díaz-Bahamondes, C. Dib, C. Diebold, S. Dima, R. Dinesh, A. Djannati-Ataï, A. Department of Physics Tokai University 4-1-1 Kita-Kaname Kanagawa Hiratsuka259-1292 Japan Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Kashiwa Chiba277-8582 Japan University of Alabama Tuscaloosa Department of Physics and Astronomy Gallalee Hall Box 870324 TuscaloosaAL35487-0324 United States Université Côte d'Azur Observatoire de la Côte d'Azur CNRS Laboratoire Lagrange France Laboratoire Leprince-Ringuet CNRS IN2P3 École polytechnique Institut Polytechnique de Paris Palaiseau91120 France Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain Instituto de Astrofísica de Andalucía CSIC Glorieta de la Astronomía s/n Granada18008 Spain Pontificia Universidad Católica de Chile Av. Libertador Bernardo O'Higgins 340 Santiago Chile IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Instituto de Física Teórica UAM CSIC Departamento de Física Teórica Universidad Autónoma de Madrid c/ Nicolás Cabrera 13-15 Campus de Cantoblanco UAM Madrid28049 Spain LUTH GEPI LERMA Observatoire de Paris Université PSL Université Paris Cité CNRS 5 place Jules Janssen Meudon92190 France INAF Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 Firenze50125 Italy INAF Osservatorio Astronomico di Roma Via di Frascati 33 Monteporzio Catone 00040 Italy TÜBITAK Research Institute for Fundamental Sciences Gebze Kocaeli41470 Turkey INFN Sezione di Napoli Via Cintia ed. G Napoli80126 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Laboratoire Univers et Particules de Montpellier Université de Montpellier CNRS IN2P3 CC 72 Place Eugène Bataillon 5 MontpellierF-34095 Cedex France Kapteyn Astronomical Institute University of Groningen Landleven 12 Groningen9747 AD Netherlands Instituto de Física de São Carlos Universidade de

Despite the advancement in background rejection techniques, observation of the very-high-energy gamma-ray sky by imaging atmospheric Cherenkov telescopes (IACTs) are subject to an irreducible background from gamma-like hadron- or electron-induced air showers. The determination of this residual background is crucial for accurate spectral and spatial measurements. The Cherenkov Telescope Array (CTA) will become the next generation of IACTs. To unveil its full potential, the improved reconstruction performance of CTA needs to be coupled with a reliable background estimate across the entire field of view. This may become especially important in the case of the planned surveys of large areas of the sky. In this contribution we will present pybkgmodel, an open-source python software package developed for CTA. It aims at providing in a consistent way the various background modelling methods, based on the experience from current IACTs such as H.E.S.S, MAGIC, and VERITAS. It is designed as a toolbox allowing a user to easily choose the optimal reconstruction approach for various target regions or a combination of several algorithms. We will introduce the design of the package as well as demonstrate its functionality using data for the CTA Large-Sized Telescope prototype (LST-1). © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

来源：评论

学校读者我要写书评

暂无评论

An improved chaotic ACO clustering algorithm 20

An improved chaotic ACO clustering algorithm

引用

20th IEEE international conference on High Performance computing and Communications (HPCC) / 16th IEEE international conference on Smart City (SmartCity) / 4th IEEE international conference on data Science and Systems (DSS)

作者： Yang, Lei Li, Kangshun Zhang, Wensheng Ke, Zhenxu Xiao, Kehui Du, Zhiguo South China Agr Univ Coll Math & Informat Guangzhou Guangdong Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China

ISBN: (纸本)9781538666142

Based on the traditional Ant Colony Optimization (ACO) clustering algorithm (ACOC), this paper proposed a new ACO algorithm for clustering, named ACO-Based Clustering Algorithm with Chaos (ACOCC). The key improvement of this algorithm is the application of chaotic function to the initialization phase and updating phase of pheromone. Applying the chaotic function to the initialization phase of pheromone can enable ants to be distributed in different states as much as possible, while applying the chaotic function to the updating phase of pheromone can bring chaotic disturbance into the algorithm, which makes the ants to explore as many paths as possible and avoids premature and converging to suboptimal solutions. The improved algorithm was implemented by MATLAB and was experimented on several public datasets, our numerical results show that the improved algorithm ACOCC can produce better optimal solution, achieve the optimal solution faster, and produce optimal solutions stably.

关键词： data mining ant colony optimization ACO clustering chaotic ant colony

来源：评论

学校读者我要写书评

暂无评论

Study on big data framework for product design 18

Study on big data framework for product design

引用

2018 international conference on data Science and Information Technology, DSIT 2018

作者： Liu, Zhuang Gong, Lin School of Mechanical Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781450365215

With the arrival of the intelligent era, Big data will play an increasingly important role in all aspects of product design. In the product design stage, comprehensive evaluations such as product quality assessment and social demand exploration are directly associated with various data and information. The advantages of big data in data mining and model prediction can be used to provide new ideas for process optimization and problem improvement of design innovation. Based on this situation, this paper proposes a big data framework based on Hadoop for product design. The framework contains the complete flow of big data analysis, and these processes are efficiently connected with good efficiency and practicality. This paper selects the data sets of product quality design and product demand design respectively, mining the design factors in the product design process through data mining technology, thus providing new ideas for product design. © 2018 Association for computing Machinery.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

DistForest: A Parallel Random Forest Training Framework based on Supercomputer 20

DistForest: A Parallel Random Forest Training Framework base...

引用

作者： Wang, Chenxu Cai, Tingting Suo, Guang Lu, Yutong Zhou, Enqiang Natl Univ Def Technol Sch Comp Sci Changsha 410073 Hunan Peoples R China Natl Supercomp Ctr Guangzhou Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781538666142

The random forest algorithm is an ensemble classifier algorithm based on the decision tree model. It has a wide range of applications in machine learning, data mining and other fields. With the emergence of big data age, the training process of random forest becomes very lengthy. Most studies speed up the training of random forests through small clusters or high performance device, however, few pay attention to high performance supercomputers. In this paper, we propose a parallel random forest training framework on supercomputers called DistForest which can utilize multiple nodes to train random forest with large data sets concurrently. Firstly, DistForest applies master-slave architecture in which system will select some nodes as the primary node to distribute the large tasks to other slave nodes. Secondly, DistForest exploits a multilevel parallel strategy which pushes small tasks to a task queue rather than continues to distribute them among other slaves. Thirdly, DistForest can use the heterogeneous architecture of supercomputers to accelerated training process. Finally, DistForest can also balance computing tasks between devices with different computing ability. Our performance results on Tianhe-2 show our implementation can acquire very high performance improvement.

关键词： Parallel Random Forest Supercomputers Speed up Framework

来源：评论

学校读者我要写书评

暂无评论

Knowledge Graph Modeling for Semantic Integration of Energy Services

Knowledge Graph Modeling for Semantic Integration of Energy ...

引用

IEEE international conference on Big data and Smart computing (BigComp)

作者： Chun, Sejin Jin, Xiongnan Seo, Seungmin Lee, Kyong-Ho Shin, Youngmee Lee, Ilwoo Yonsei Univ Dept Comp Sci Seoul South Korea ETRI IoT Res Div Daejeon South Korea

ISBN: (纸本)9781538636497

The forthcoming smart-grid is expected to provide advanced energy services more efficiently and eco-friendly with an integrated network of various information such as a smart meter and social networks. As an information model of expressing such an integrated network, a knowledge graph (KG) represents a formal and common specification of concepts and relations in a specific domain. It is essential to leverage KGs for the interoperability, reusability, and scalability of smart-grid applications. However, existing KGs have limitations in accommodating detailed descriptions of energy services. In this paper, we propose an energy knowledge graph, which provides the semantic integration of various energy services. The proposed model also provides the detailed description of a micro-grid community. To verify the proposed model, we present and discuss its use-cases based on energy service scenarios.

关键词： Smart Grid Knowledge Graph Micro-grid Semantic Web

来源：评论

学校读者我要写书评

暂无评论

Comparison of Different Machine Learning Methods to Forecast Air Quality Index 6th

Comparison of Different Machine Learning Methods to Forecast...

引用

6th international conference on Frontier computing, FC 2018

作者： Liu, Bo Shi, Chao Li, Jianqiang Li, Yong Lang, Jianlei Gu, Rentao Beijing Advanced Innovation Center for Future Internet Technology Beijing University of Technology Beijing100124 China Faculty of Information Technology School of Software Engineering Beijing University of Technology Beijing100124 China Key Laboratory of Beijing on Regional Air Pollution Control Beijing University of Technology Beijing100124 China College of Environmental and Energy Engineering Beijing University of Technology Beijing100124 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789811336478

In recent years, more and more people have been plagued by respiratory diseases. The air quality, which is characterized by inhalable particles and fine particles, has attracted increasing attention. Accurately monitor and forecast the quality of air could not only help the government conduct interventions to alleviate the air pollution earlier, but also alert relevant people who suffer from respiratory diseases. In order to develop effective Air Quality Index (AQI) prediction models, this paper compared the performance of different Machine Learning (ML) methods and feature selection methods. First the air quality data in Beijing from 2016 to 2017 were collected. Then Multi-Linear Regression (MLR), Random forest Regression (RFR), BP Neural Network (BPNN) and Support Vector Regression (SVR) algorithm were trained on 10-fold cross validation. Correlation coefficient (R), mean absolute error (MAE) and root mean square error (RMSE) were used as evaluation metrics. The experimental results showed that the performance of SVR and BPNN were similarly well. MLR had the worst performance, which was possibly caused by a small feature dimension, and RFR had higher accuracy and better generalization capability than the other models, probably because the algorithm of regression tree in random forest included the interaction of variables. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Decision trees

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336页 << < 26 27 28 29 30 31 32 33 34 35 > >>

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：