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

23,206 篇 会议
2,925 篇 期刊文献
16 篇 学位论文

馆藏范围

26,147 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,635 篇 工学
- 3,385 篇 计算机科学与技术...
- 3,129 篇 电气工程
- 1,801 篇 信息与通信工程
- 637 篇 控制科学与工程
- 536 篇 软件工程
- 480 篇 仪器科学与技术
- 299 篇 测绘科学与技术
- 298 篇 机械工程
- 284 篇 生物医学工程（可授...
- 148 篇 电子科学与技术（可...
- 114 篇 生物工程
- 107 篇 交通运输工程
- 107 篇 环境科学与工程（可...
- 75 篇 网络空间安全
- 56 篇 航空宇航科学与技...
- 41 篇 材料科学与工程（可...
839 篇 理学
- 192 篇 物理学
- 157 篇 生物学
- 136 篇 地球物理学
- 125 篇 数学
- 122 篇 系统科学
- 96 篇 地理学
- 49 篇 化学
- 43 篇 统计学（可授理学、...
524 篇 管理学
- 479 篇 管理科学与工程(可...
490 篇 医学
- 367 篇 临床医学
- 99 篇 基础医学(可授医学...
195 篇 农学
- 99 篇 作物学
- 80 篇 农业资源与环境
75 篇 文学
- 70 篇 新闻传播学
23 篇 教育学
21 篇 经济学
19 篇 艺术学
13 篇 法学
7 篇 军事学
2 篇 历史学

主题

26,147 篇 classification a...
6,409 篇 feature extracti...
5,157 篇 training
4,576 篇 accuracy
4,334 篇 support vector m...
3,145 篇 machine learning...
2,640 篇 prediction algor...
2,633 篇 clustering algor...
2,490 篇 algorithm design...
2,347 篇 data mining
2,228 篇 machine learning
1,576 篇 data models
1,368 篇 deep learning
1,337 篇 optimization
1,325 篇 decision trees
1,158 篇 testing
1,150 篇 predictive model...
1,113 篇 computational mo...
1,083 篇 neural networks
1,021 篇 databases

机构

62 篇 chitkara univers...
23 篇 centre of resear...
23 篇 college of infor...
19 篇 school of comput...
18 篇 tsinghua univers...
18 篇 university of ch...
17 篇 chitkara centre ...
17 篇 school of inform...
17 篇 department of co...
16 篇 school of comput...
16 篇 school of comput...
16 篇 school of electr...
14 篇 computer science...
14 篇 univ chinese aca...
14 篇 microsoft resear...
14 篇 school of comput...
13 篇 school of electr...
13 篇 school of electr...
12 篇 department of in...
11 篇 state key labora...

作者

29 篇 wei li
22 篇 hui wang
22 篇 jun wang
21 篇 lei wang
17 篇 xia sun
17 篇 yang yang
16 篇 jing zhang
15 篇 jun zhang
15 篇 liu yang
14 篇 xi chen
14 篇 li zhang
14 篇 jie li
13 篇 jian wang
13 篇 rakesh kumar
13 篇 jie yang
13 篇 jun shi
13 篇 chen chen
12 篇 bing xue
12 篇 ahmad jalal
12 篇 xuegang hu

语言

26,011 篇 英文
95 篇 其他
33 篇 中文
4 篇 土耳其文
2 篇 法文
1 篇 西班牙文
1 篇 俄文

检索条件"主题词=Classification Algorithms"

共 26147 条记录，以下是4901-4910 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：

Application of Naïve Bayes Algorithm for Sentiment classification of Subtle Sandwich Feedback from Google Forms

Application of Naïve Bayes Algorithm for Sentiment Classifi...

引用

International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Justin S Hilmansah Imanda D Sabiella Nugroho J Setiadi Creativepreneurship Binus Business School Bina Nusantara University Bandung Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

Sentiment analysis is a powerful method for understanding customers' opinions and feelings towards a product or service. This research aims to analyze customer sentiments about Subtle Sandwich products using Naïve Bayes algorithm, with the goal of understanding customer perceptions of Subtle Sandwich. The Naïve Bayes algorithm classifies customer sentiment into three categories, including positive, negative, and neutral. Sentiment data were collected through a Google Form questionnaire distributed to customers. Data processing was done using RapidMiner application along with CRISP-DM data mining design and preparation method approach. The model achieved an accuracy of 78.07 percent, with recall rates of 76.96 percent for positive, 81.37 percent for negative, and 79.07 percent for neutral sentiments. Using the Naïve Bayes algorithm and WordCloud operator, we were able to identify frequently used keywords in the dataset to provide deeper insights for actionable recommendations for improving product quality, consistency, and business strategies.

关键词： Sentiment analysis Accuracy Supply chains Product design Bayes methods classification algorithms Quality assessment Internet Data mining Business

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous classifier model for E-mail spam classification using FSO feature selection method

Heterogeneous classifier model for E-mail spam classificatio...

引用

International Conference on Inventive Computation Technologies (ICICT)

作者： Sathishkumar Easwaramoorthy Sankar Thamburasa Karrothu Aravind S. Bharath Bhushan Hariharan Rajadurai Research Scholar School of Information Technology and Engineering Information security Analyst Synophic System Private limited Bangalore India VIT University Vellore Tamil Nadu IN

ISBN: (纸本)9781509012862

In this Computer world, E-mail is one of the popular modes of communication due to its easy accessibility and low cost. Due to the advantages of time, speed and cost effectiveness, a lot of people use it for commercial advertisement purposes resulting in unnecessary e-mails at user inboxes called spam. Spam is the unnecessary and unwanted commercial e-mail. It is also known as junk e-mail. It is sending unnecessary e-mail message with profit-making data to in discriminated group of recipients. It is waste of storage space, time, and network bandwidth. E-mail classifier classifies the group of mails into ham and spam based on its data content. E-mail classifications system, which clean the spam e-mails from inbox, move it to the spam folder. The proposed e-mail classification system includes two stages, such as training stage and testing stage. Initial stage, input e-mail message is sent to the feature selection module to pick the suitable feature for spam classification. In this paper, firefly and GSO algorithm is efficiently combined to pick the appropriate features from the big dimensional area using correlation. Once the finest feature space is determined through FSO algorithm, the E-mail classification is accomplished using weighted based majority voting system. The classifiers applied for classifying e-mails are naive bayes algorithm, neural networks and decision tree. The UCI spambase dataset is utilized for e-mail spam classification. The research result validation of the proposed technique is made through evaluation metrics such as, precision, recall and accuracy.

关键词： classification algorithms Unsolicited electronic mail Algorithm design and analysis Decision trees Neural networks Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Automatic classification of combined analog and digital modulation schemes using feedforward neural network

Automatic classification of combined analog and digital modu...

引用

AFRICON Conference

作者： Jide Julius Popoola Rex van Olst School of Electrical and Information Engineering University of the Witwatersrand Johannesburg South Africa

This paper presents an artificial neural network based automatic modulation classifier system which can be used to classify combined analog and digital modulation schemes. Four best known analog modulation schemes and five corresponding digital modulation schemes were considered. An approach that involves three different steps in developing an automatic modulation classification is presented. The first step involves the extraction of the statistical feature keys used as the inputs to the classifier. The statistical feature keys are extracted from instantaneous amplitude, instantaneous frequency and phase of the simulated signals using MATLAB code. The second step involves the development of the automatic modulation classifier based on a backpropagation neural network algorithm. The third step of the methodology involves the performance evaluation of the developed automatic modulation classifier with a related study from the research literature. Results obtained show that the developed classifier is accurate and sensitive to classification of the nine modulation schemes considered with an average success rate above 99.0%.

关键词： Neurons classification algorithms Feature extraction Signal to noise ratio Frequency modulation Artificial neural networks

来源：评论

学校读者我要写书评

暂无评论

An Improved Algorithm for Chest X-Ray Image classification

An Improved Algorithm for Chest X-Ray Image Classification

引用

International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Bayu Adhi Nugroho UIN Sunan Ampel Surabaya

ISBN: (纸本)9781665401524

The application of a Deep Neural Network for medical image classification has been known widely to help the tasks of an accurate doctor assessment. One of the applications is the classification of diseases from Chest X-Ray images. The NIH Chest X-Ray dataset is the most popular and the most prominent medical images database in the field. Several approaches have been made to improve the classification of the 14 classes from the dataset, including modifying network layers, handcrafting the dataset, and conducting smart-augmentation. We propose a weight modification algorithm to overcome the class imbalance problem. Hence, our objective is to improve the classification. The work's novelty is the proposed framework to improve the classification performance, which includes: (i) a novel weight calculation formula, (ii) the real-dataset augmentation into the training data. Experimental results are provided to show the improved classification performance. Our experiments are based on the standardized split-sets, which are also used by previous researches. The steady-state experiment settings are required to achieve acceptable results for the dataset. This study contributes to (i) the further cost-sensitive algorithm to train an imbalance Chest X-Ray dataset, also (ii) we provide results under identical settings compared to the previous study.

关键词： Deep learning Seminars Neural networks Training data classification algorithms Steady-state Task analysis

来源：评论

学校读者我要写书评

暂无评论

SRFW: a simple, fast and effective text classification algorithm

SRFW: a simple, fast and effective text classification algor...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zhi-Hong Deng Shi-Wei Tang Dong-Qing Yang Ming Zhang Xiao-Bin Wu Meng Yang Department of Computer Science and Technology Peking University Beijing China Center for Information Sciences National Laboratory on Machine Perception Peking University Beijing China

Text classification is a powerful technique for automating assignment of documents to topic hierarchies. Although there are a number of text classification algorithms, most of them are either inefficient or too complex. We present a linear text classification algorithm called SRFW, which is fast, effective and easily used. SRFW obtains relevance factors. For new unlabelled documents, SRFW adopts sum of weights based on relevance factors to obtain the probability that these documents belong to each category and assigns them to categories that have the biggest probability. We have evaluated our algorithm on a subset of Reuters-21578 and 20-newsgroups text collections and compared it against k-NN and SVM. Experimental results show that SRFW is competitive with k nearest neighbor (k-NN) and support vector machines (SVM), while SRFW is much simpler and faster than them.

关键词： Text categorization classification algorithms Support vector machines Support vector machine classification Nearest neighbor searches Probability Neural networks Computer science Laboratories Electronic mail

来源：评论

学校读者我要写书评

暂无评论

An iterative algorithm for optimal style conscious field classification

An iterative algorithm for optimal style conscious field cla...

引用

International Conference on Pattern Recognition

作者： P. Sarkar Statistical Pattern and Image Analysis Area Information Sciences and Technologies Laboratory Palo Alto Research Center Inc.orporated Palo Alto CA USA

Modeling consistency of style in isogenous fields of patterns (such as character patterns in a word from the same font or writer) can improve classification accuracy. Since such patterns are interdependent, the Bayes classifier requires maximization of a probability score over all field-labels, which are exponentially more numerous with increasing field length. The iterative field classification algorithm prioritizes field-labels, for computation of probability scores, according to an upper bound on the score. Factorizability of the upper bound score allows dynamic prioritization of field-labels. Experiments on classification of numeral field patterns demonstrate computational efficiency of the algorithm.

关键词： Iterative algorithms Upper bound Pattern recognition Optical character recognition software classification algorithms Image analysis Laboratories Speech

来源：评论

学校读者我要写书评

暂无评论

WeChat Text Messages Service Flow Traffic classification Using Machine Learning Technique

WeChat Text Messages Service Flow Traffic Classification Usi...

引用

International Conference on IT Convergence and Security (ICITCS)

作者： Muhammad Shafiq Xiangzhan Yu Asif Ali Laghari School of Computer Science and Technology Harbin Institute of Technology Harbin PR China

ISBN: (纸本)9781509037667

In this era of information technology, network traffic classification is a very important and hot topic from the perspective of network security and management due to substantial use of dynamic applications. Numerous research models have been proposed in network traffic classification to classify different types of applications and achieve significant accuracy results. However, no work has been done to classify WeChat messages flow traffic. WeChat is a free instant messaging application. Hence, it is very important to classify WeChat text messages traffic. In this paper, we classify WeChat messages flows traffic using two different data sets, which are first captured using Wireshark tool from two different locations network environments, Harbin Institute of Technology Lab and Jinyuan Hotel and then 50 features are extracted from captured traffic. After that four machine learning algorithms SVM, C4.5, Bayes Net and nalve Byes are applied to classify the WeChat text messages traffic. Experimental results show that all classifiers give very high accuracy results using two different data sets. Using Jinyuan data set SVM and C4.5 decision tree algorithm give 100% accuracy result as compared to Bayes Net and Naive Bayes algorithm and using Harbin Institute of Technology Lab data set all classifiers give 99.7% high accuracy results.

关键词： Machine learning algorithms Support vector machines Training classification algorithms Feature extraction Software Telecommunication traffic

来源：评论

学校读者我要写书评

暂无评论

CART Decision Tree Combined with Boruta Feature Selection for Medical Data classification

CART Decision Tree Combined with Boruta Feature Selection fo...

引用

IEEE International Conference on Big Data Analysis (ICBDA)

作者： Rong Tang Xiaojun Zhang School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728141114

ISBN: (纸本)9781728141121

As the data stored in the medical database may contain missing values and redundant data, making medical data classification challenging. According to the characteristics of the medical data set containing missing values, the classification and regression (CART) algorithm is naturally thought of. However, when the CART algorithm processes a data set with too many categories, the error rate will increase rapidly and easily lead to overfitting. This paper proposes a solution for the characteristics of medical data sets and the shortcomings of CART algorithm. In order to improve the accuracy of medical data, the Boruta method was proposed to reduce the dimension. Then CART algorithm is used to classify feature subset. The data set on UCI was used in the experiment, and the results show that the accuracy of the CART algorithm is improved.

关键词： Medical diagnostic imaging Feature extraction classification algorithms Training Indexes Diseases Decision trees

来源：评论

学校读者我要写书评

暂无评论

Lower bounds in classification for feature and algorithm selection

Lower bounds in classification for feature and algorithm sel...

引用

International Conference on Space Technology (ICST)

作者： George A. Lampropoulos Chuhong Fei Ting Liu Abhijit Sinha Xia Liu A.U.G. Signals Limited Toronto ONT Canada

The objective of this paper is to study recent advancements in estimation lower bound classification results. These lower bounds are estimated for a given set of features, targets, Signal to Noise Ratios (SNRs), and representative clutter environments. The motivation of this work comes from the desire to know the best achievable classification results for a given set of features at a range of SNRs and sensor data. This will assist the end user and classifier designer to select features that maximize the theoretical classification performance (i.e. minimize the classification errors in the confusion matrix tables). It will also assist in selecting the suitable classification algorithms approaching the lower theoretical classification bounds. The theoretical bounds used in this paper in our experimental examples are based on the Bayesian approach. However, other bounds are also reviewed. These results can be applied for selecting features and classifiers for earth and deep space observations and surveillance.

关键词： Training Bagging Boosting classification algorithms Support vector machine classification Feature extraction Decision trees

来源：评论

学校读者我要写书评

暂无评论

Sentiment classification for Chinese product reviews using an unsupervised Internet-based method

Sentiment classification for Chinese product reviews using a...

引用

International Conference on Management Science and Engineering (ICMSE)

作者： Rob Law Zi-qiong Zhang Yi-jun Li Qiang Ye Hong Kong Polytechnic University Hong Kong Sch. of Manage. Harbin Inst. of Technol. Harbin Hong Kong Polytechnic University Kowloon HK

Sentiment classification aims at mining opinions of customers for a certain product by automatically classifying the reviews into positive or negative opinions. With the fast developing of World Wide Web applications, sentiment classification would have huge opportunity to help automatic analysis of customerspsila opinions from the web information. Opinion mining will benefit both consumers and sellers. Up to now, it is still a complicated task with great challenge. Though some pioneer researches explored the approaches for English review classification, few works have been done on sentiment classification for Chinese reviews. In this paper, we focus on a specific domain-cell phone review and propose an Internet-based approach for Chinese product review mining. The experimental results show the effectiveness of the proposed approach in sentiment classification for Chinese product reviews.

关键词： Internet Conference management Technology management Engineering management Web sites Information analysis Cellular phones classification algorithms Labeling Buildings

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500页 << < 487 488 489 490 491 492 493 494 495 496 > >>

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：