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

6,256 篇 会议
4,865 篇 期刊文献
48 册 图书

馆藏范围

11,169 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

6,520 篇 工学
- 4,230 篇 计算机科学与技术...
- 3,360 篇 软件工程
- 1,087 篇 信息与通信工程
- 965 篇 生物工程
- 949 篇 控制科学与工程
- 842 篇 生物医学工程（可授...
- 733 篇 电气工程
- 665 篇 电子科学与技术（可...
- 581 篇 光学工程
- 514 篇 化学工程与技术
- 411 篇 材料科学与工程（可...
- 321 篇 仪器科学与技术
- 320 篇 机械工程
- 238 篇 动力工程及工程热...
4,380 篇 理学
- 1,593 篇 物理学
- 1,560 篇 数学
- 1,411 篇 生物学
- 612 篇 统计学（可授理学、...
- 604 篇 化学
- 282 篇 系统科学
1,649 篇 管理学
- 861 篇 管理科学与工程(可...
- 836 篇 图书情报与档案管...
- 549 篇 工商管理
1,057 篇 医学
- 890 篇 临床医学
- 690 篇 基础医学(可授医学...
- 340 篇 药学(可授医学、理...
- 256 篇 公共卫生与预防医...
445 篇 教育学
- 289 篇 教育学
- 201 篇 心理学(可授教育学...
394 篇 法学
- 367 篇 社会学
211 篇 农学
175 篇 经济学
64 篇 文学
25 篇 哲学
13 篇 历史学
13 篇 艺术学
10 篇 军事学

主题

275 篇 computer science
175 篇 deep learning
160 篇 machine learning
157 篇 semantics
154 篇 computational mo...
127 篇 accuracy
122 篇 feature extracti...
112 篇 training
111 篇 artificial intel...
110 篇 neural networks
105 篇 visualization
99 篇 support vector m...
96 篇 students
95 篇 cognitive scienc...
91 篇 computer archite...
87 篇 predictive model...
82 篇 reinforcement le...
80 篇 data mining
79 篇 humans
75 篇 decision making

机构

159 篇 computer science...
103 篇 department of co...
100 篇 computer science...
61 篇 moe key lab of a...
52 篇 key laboratory o...
46 篇 bioinformatics a...
44 篇 department of ph...
44 篇 school of comput...
42 篇 computer science...
40 篇 renewable and su...
39 篇 centre for cogni...
35 篇 department of el...
30 篇 department of ph...
27 篇 computer science...
27 篇 photonics initia...
27 篇 photonics initia...
27 篇 cognitive scienc...
27 篇 bioinformatics a...
25 篇 school of physic...
25 篇 computer science...

作者

192 篇 zhao hai
107 篇 bens pardamean
96 篇 pardamean bens
86 篇 zhang zhuosheng
80 篇 gaol ford lumban
58 篇 heryadi yaya
57 篇 warnars harco le...
43 篇 prabowo harjanto
38 篇 andrea alù
34 篇 kersting kristia...
33 篇 ivan i. smalyukh
28 篇 kono junichiro
28 篇 yaya heryadi
26 篇 anggreainy maria...
23 篇 yu kai
22 篇 rahutomo reza
22 篇 muhammad zarlis
21 篇 agung trisetyars...
21 篇 hidayat alam ahm...
21 篇 wang deliang

语言

10,582 篇 英文
521 篇 其他
54 篇 中文
5 篇 日文
4 篇 西班牙文
2 篇 德文
2 篇 法文
2 篇 斯洛文尼亚文
1 篇 朝鲜文

检索条件"机构=Department of Computer Science and Cognitive Science Program"

共 11169 条记录，以下是631-640 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：

Aspect-based Sentiment Analysis using Long Short-term Memory Model for Leveraging Restaurant Service Management

Aspect-based Sentiment Analysis using Long Short-term Memory...

引用

2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Fitria Murad, Dina Tho, Cuk Hashimoto, Kiyota BINUS Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

In general, the hospitality industry has been acknowledged as a major sector that gives a high contribution to economic development in many countries including Indonesia. For that reason, many initiatives have been implemented to help the growth of the hospitality industry in many countries including Indonesia to rebound from the harsh impact of the Covid-19 Pandemic. One such initiative is improving restaurant services as the main sector of the hospitality industry. This paper presents empirical results of sentiment analysis as a means to assess the quality of restaurant services as the first step to improving service quality. In particular, this study explores the aspect-based sentiment analysis method to identify some aspects of restaurant service which need improvement by learning the polarity of customers toward the restaurant services without having to meet the customers directly. By using the aspect-based sentiment analysis method, the customer sentiments comprising opinions, sentiments, evaluations, attitudes, and emotions from restaurant service can be analyzed using customers' online reviews as input. The main experiment findings showed that the Long Short-term Memory model can achieve high performance in predicting aspect polarization in restaurant service reviews. Other findings suggest that Sigmoid as an activation function achieved 0.97 average training accuracy and 0.69 average testing accuracy giving a better performance to the model in comparison to ReLU, Tanh, and ELU activation functions. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Protein Structure Prediction Using Dynamic Speciation Evolutionary Algorithm with Aggregated Problem Information 21

Protein Structure Prediction Using Dynamic Speciation Evolut...

引用

21st IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2024

作者： Parpinelli, Rafael Stubs Wojeicchowski, Nicholas Will, Nilcimar Neitzel State University of Santa Catarina Graduate Program in Applied Computing Joinville Brazil State University of Santa Catarina Computer Science Department Joinville Brazil

ISBN: (纸本)9798350356632

Protein structure prediction in three dimensions represents a fundamental challenge in Structural Bioinformatics. Leveraging problem-specific information such as fragment insertion, secondary structure, and contact maps can significantly enhance the exploration of the search space. In this study, an evolutionary algorithm is introduced, which incorporates such problem information for protein structure prediction. The proposed method employs a dynamic speciation technique alongside fragment insertion to foster population diversity. To ensure a rich variety of fragments, a fragment library is constructed using the Rosetta Quota protocol. Additionally, information from contact maps and secondary structure is integrated into two selection strategies to facilitate a more thorough exploration of the conformational search space. The results of an experimental evaluation involving 9 proteins are presented, demonstrating competitive performance compared to existing literature. Evaluation metrics include RMSD, GDT, and processing time. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

A Performance Study of Selected Machine Learning Techniques for Predicting Heart Diseases 2nd

A Performance Study of Selected Machine Learning Techniques ...

引用

2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Olorunfemi, Blessing Oluwatobi Ogunde, Adewale Opeoluwa Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Li, Chun-Ta Faculty of Natural Sciences Department of Computer Science Redeemer’s University Osun Nigeria Department of Computer Science Bowen University Iwo Nigeria Faculty of Information and Communication Sciences Department of Computer Science University of Ilorin Ilorin240003 Nigeria Faculty of Engineering Department of Electrical and Electronics Engineering University of Lagos Lagos Akoka100213 Nigeria Bachelor’s Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City24206 Taiwan

ISBN: (纸本)9789819777853

Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosis is a difficult process that requires technical skills and accuracy to complete. With improvements in technology, computing has lent its voice to simplify the diagnosis of various health problems. Machine learning uses past or existing history to predict future results. Various machine learning techniques have been developed over the years and used in predicting heart diseases with various levels of performance. Identifying the best-suited machine learning technique to use for prediction purposes can be a challenging task. This research work analyses the performance of seven (7) machine learning techniques, comprising AdaBoost Algorithm, KNN, Logistic Regression, Naïve Bayes Classifier, Random Forest, SVM, and XGBoost. The heart disease dataset was downloaded from the UCI repository and analysed using Python programming language in the Jupyter Notebook environment. A comparative analysis of the seven (7) techniques was performed based on Accuracy, Precision, and Recall. From the results obtained, KNN, Random Forest, and XGBoost showed superior performance over the others with an accuracy of 100%, AdaBoost Algorithm followed with an accuracy of 92.2%, SVM followed with an accuracy of 91.71%, Naïve Bayes Classifier followed with an accuracy of 88.29% while Logistic Regression has the least accuracy of 86.34%. KNN, RF, and XGBoost outperformed AdaBoost, SVN, and LR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

引用

2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Yanfi, Yanfi Heryadi, Yaya Lukas, Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University Binus Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy. © 2022 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

The Effect of Viewpoint Change Strategies on Multi-View Video and Audio Transmission QoE Over ICN/CCN 38

The Effect of Viewpoint Change Strategies on Multi-View Vide...

引用

38th IEEE Region 10 Conference, TENCON 2023

作者： Nunome, Toshiro Takada, Yoshiyuki Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350302196

In this paper, we exploit caches on intermediate nodes for QoE enhancement of multi-view video and audio transmission over ICN/CCN by controlling the content request start timing of consumers. We assume the selected single viewpoint transmission method;a consumer receives video and audio streams of a requested viewpoint. We perform a simple experiment with two consumers. When the consumers play video and audio with the time difference, we assess the effect of cached content by the former consumer's request on the output quality of the latter consumer. We deal with two types of viewpoint change strategies for the former consumer, which affect the efficiency of cache utilization. From the assessment results, we see that cache utilization has an important factor in enhancing QoE. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analyzing Nickel Stock Price Prediction: A Comparative Study of Long Short-Term Memory and Convolutional Neural Network Models

Analyzing Nickel Stock Price Prediction: A Comparative Study...

引用

IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

作者： Ferry Irwanto Muhammad Farrell Hafizh Sasongko Stevanus Febrian Alexander Agung Santoso Gunawan Karli Eka Setiawan Data Science Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350353464

ISBN: (纸本)9798350353471

This research delves to predict PT Vale Indonesia Tbk stock price as an experiment on Indonesian stock using three models: naïve, LSTM, and 1D-CNN. Our analysis emphasizes the importance of matching model architectures to data properties. We compare models' performance with fiveday window for predict one-day prediction output. Interestingly, the single-layer LSTM outperforms the 1D-CNN even with similar hyperparameters, showcasing its strength in capturing long-term temporal dependencies crucial for nickel prices. While the 1D-CNN excels at identifying short-term patterns, its limited receptive field hinders long-term dependence. Recognizing the potential of both models, we encourage exploring hybrid architectures combining LSTM and CNN strengths for further improvement in financial forecasting. The experiment result shows single-layer LSTM outperforms a 1D-CNN with similar settings.

关键词： Analytical models Predictive models Nickel Data models Communications technology Fourth Industrial Revolution Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Restaurant Customer Feedback Sentiment Analysis using Aspect Embedding Long Short-term Memory Model

Restaurant Customer Feedback Sentiment Analysis using Aspect...

引用

2023 International Conference on computer science, Information Technology and Engineering, ICCoSITE 2023

ISBN: (纸本)9798350320954

In the past ten years, there has been a proliferation of unstructured textual data from a variety of fields, allowing for the analysis of the sentiment polarity of the text authors in each of those datasets. To analyze sentiment polarity from unstructured data, machine learning tasks such as aspect-based sentiment analysis are used. The public dataset of restaurant patron feedback was used as the input for this study's empirical results of aspect-based sentiment analysis utilizing the Aspect Embedding Long Short-Term Memory model. The primary experiment's results show that the aspect embedding long short-term memory model can predict aspect sentiment polarization from customer feedback to restaurant service and aspect text representation (aspect text embedding) as input with excellent performance. For example, the Aspect Embedding Long Short-term Memory model, which uses ReLU as its activation function in the Dense layer tends to achieve higher performance (0.97 average accuracies) than the same model equipped with Sigmoid, and Tanh functions which achieve 0.954 and 0.956 average training accuracy respectively. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Classification of Health Insurance Fraud Risk with Machine Learning

Classification of Health Insurance Fraud Risk with Machine L...

引用

Information Technology Research and Innovation (ICITRI), International Conference on

作者： Muhammad Kent Al-Ghazi Ryan Bertrand Muhammad Dzul Qarrnayn Destra Alexander Agung Santoso Gunawan Karli Eka Setiawan Data Science Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350376210

ISBN: (纸本)9798350376227

Health insurance is a useful service that can help its users gain lifesaving medical aid when they are in need. However, health insurance is also exploitable to insurance fraud through the falsification of information to increase the amount of reimbursement and cause massive loss of funds to the insurance provider. We propose the usage of machine learning to accurately determine potential health insurance fraud. The objective of conducting this research is to determine which features are the most important to determine healthcare insurance fraud. This research used a dataset provided in Kaggle titled Healthcare Provider Fraud Detection Analysis using Random Forest Classifier and Logistic Regression. The best-performing model in this test, the Logistic Regression, is then used to which features are the most important for the classification. Our research shows that the most important feature in detecting health insurance fraud is the amount of money reimbursed associated with a provider. The Logistic Regression model achieved an accuracy of 0.90, precision of 0.93, recall of 0.91, and an F1 Score of 0.90, outperforming the Random Forest model in comparative analysis.

关键词： Logistic regression Analytical models Technological innovation Accuracy Insurance Medical services Feature extraction Fraud Information technology Random forests

来源：评论

学校读者我要写书评

暂无评论

MEM-Based Pangenome Indexing for k-mer Queries 24

MEM-Based Pangenome Indexing for k-mer Queries

引用

24th International Workshop on Algorithms in Bioinformatics, WABI 2024

作者： Hwang, Stephen Brown, Nathaniel K. Ahmed, Omar Y. Jenike, Katharine M. Kovaka, Sam Schatz, Michael C. Langmead, Ben XDBio Program Johns Hopkins University BaltimoreMD United States Department of Computer Science Johns Hopkins University BaltimoreMD United States

ISBN: (纸本)9783959773409

Pangenomes are growing in number and size, thanks to the prevalence of high-quality long-read assemblies. However, current methods for studying sequence composition and conservation within pangenomes have limitations. Methods based on graph pangenomes require a computationally expensive multiple-alignment step, which can leave out some variation. Indexes based on k-mers and de Bruijn graphs are limited to answering questions at a specific substring length k. We present Maximal Exact Match Ordered (MEMO), a pangenome indexing method based on maximal exact matches (MEMs) between sequences. A single MEMO index can handle arbitrary-length queries over pangenomic windows. MEMO enables both queries that test k-mer presence/absence (membership queries) and that count the number of genomes containing k-mers in a window (conservation queries). MEMO's index for a pangenome of 89 human autosomal haplotypes fits in 2.04 GB, 8.8× smaller than a comparable KMC3 index and 11.4× smaller than a PanKmer index. MEMO indexes can be made smaller by sacrificing some counting resolution, with our decile-resolution HPRC index reaching 0.67 GB. MEMO can conduct a conservation query for 31-mers over the human leukocyte antigen locus in 13.89 seconds, 2.5× faster than other approaches. MEMO's small index size, lack of k-mer length dependence, and efficient queries make it a flexible tool for studying and visualizing substring conservation in pangenomes. © Stephen Hwang, Nathaniel K. Brown, Omar Y. Ahmed, Katharine M. Jenike, Sam Kovaka, Michael C. Schatz, and Ben Langmead

关键词： Comparative genomics Compressed indexing Pangenomics

来源：评论

学校读者我要写书评

暂无评论

The Effect of Bitrate Control Methods of MPEG-DASH Streaming on Multi-View Video and Audio QoE

The Effect of Bitrate Control Methods of MPEG-DASH Streaming...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Nunome, Toshiro Wakayama, Yamato Nagoya Institute of Technology Computer Science Program Department of Engineering Graduate School of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350324174

This paper investigates the effect of bitrate control methods on QoE of multi-view video and audio streaming with MPEG-DASH. We adopt three bitrate control methods for conventional single-view video streaming to the MVV-A system with MPEG-DASH. We conduct a subjective experiment changing available network bandwidth and investigate the effect of the methods on QoE. © 2023 IEEE.

关键词： Video streaming

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 << < 60 61 62 63 64 65 66 67 68 69 > >>

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：