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

4,303 篇 会议
103 册 图书
50 篇 期刊文献

馆藏范围

4,456 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,583 篇 工学
- 2,439 篇 计算机科学与技术...
- 1,808 篇 软件工程
- 365 篇 信息与通信工程
- 292 篇 控制科学与工程
- 264 篇 电气工程
- 173 篇 生物工程
- 94 篇 化学工程与技术
- 78 篇 生物医学工程（可授...
- 74 篇 机械工程
- 72 篇 网络空间安全
- 61 篇 电子科学与技术（可...
- 49 篇 仪器科学与技术
- 40 篇 安全科学与工程
- 36 篇 光学工程
- 35 篇 交通运输工程
- 32 篇 材料科学与工程（可...
807 篇 管理学
- 553 篇 图书情报与档案管...
- 314 篇 管理科学与工程(可...
- 106 篇 工商管理
679 篇 理学
- 306 篇 数学
- 178 篇 生物学
- 158 篇 物理学
- 119 篇 统计学（可授理学、...
- 100 篇 化学
- 68 篇 系统科学
93 篇 医学
- 73 篇 临床医学
- 65 篇 基础医学(可授医学...
- 50 篇 公共卫生与预防医...
75 篇 法学
- 68 篇 社会学
74 篇 教育学
- 73 篇 教育学
35 篇 文学
28 篇 农学
25 篇 经济学
4 篇 艺术学
2 篇 军事学

主题

1,077 篇 natural language...
322 篇 semantics
315 篇 natural language...
297 篇 natural language...
236 篇 knowledge engine...
226 篇 data mining
216 篇 machine learning
168 篇 information retr...
154 篇 accuracy
153 篇 artificial intel...
152 篇 deep learning
152 篇 training
135 篇 computational mo...
123 篇 knowledge based ...
123 篇 sentiment analys...
119 篇 ontologies
114 篇 large language m...
111 篇 computer science
111 篇 databases
111 篇 feature extracti...

机构

27 篇 faculty of engin...
26 篇 maharishi school...
22 篇 school of inform...
16 篇 institute of inf...
15 篇 centre of interd...
15 篇 school of cyber ...
14 篇 lovely professio...
13 篇 school of comput...
13 篇 department of co...
12 篇 beijing universi...
12 篇 school of comput...
11 篇 school of comput...
10 篇 national laborat...
10 篇 knowledge engine...
10 篇 institute of com...
9 篇 school of comput...
9 篇 beijing univ pos...
9 篇 university of ch...
9 篇 school of electr...
9 篇 moe-ms key labor...

作者

67 篇 fuji ren
37 篇 ren fuji
16 篇 bo xu
14 篇 shingo kuroiwa
14 篇 yixin zhong
14 篇 xiaojie wang
11 篇 tiejun zhao
10 篇 dongfeng cai
10 篇 lei li
10 篇 f. ren
10 篇 jingbo zhu
9 篇 s. kuroiwa
8 篇 wenju liu
8 篇 tianrui li
8 篇 zhu jingbo
8 篇 degen huang
7 篇 tanioka tetsuya
7 篇 tingting he
7 篇 guiping zhang
7 篇 vogelsang andrea...

语言

3,841 篇 英文
597 篇 其他
32 篇 中文

检索条件"任意字段=2003 International Conference on Natural Language Processing and Knowledge Engineering"

共 4456 条记录，以下是881-890 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：

knowledge EXTRACTION METHOD TO SUPPORT DOMAIN INTEGRATED DESIGN METHODOLOGY

KNOWLEDGE EXTRACTION METHOD TO SUPPORT DOMAIN INTEGRATED DES...

引用

ASME international Design engineering Technical conferences / 42nd Annual Computers and Information in engineering conference (IDETC-CIE)

作者： Sun, Siyuan Velivela, Pavan Tejaswi Zeng, Yong Zhao, Yaoyao Fiona McGill Univ Dept Mech Engn Montreal PQ Canada Concordia Univ Concordia Inst Informat Syst Engn Montreal PQ Canada

ISBN: (纸本)9780791886212

Nowadays, bio-inspiration has enhanced the creation of sustainable and innovative solutions to modern engineering problems. Nature could inspire mechanical engineers to develop innovative ideas as a great source for multifunctional and optimized designs. However, it is very difficult to extract desired design knowledge from primarily text-based databases and mainly focus on describing the biological system. The main objective of this study is to build a multi-label classification system to classify bio-inspired designs to support the Domain Integrated Design methodology. The proposed system integrates NLP and text mining with several machine learning models to learn and predict the functionalities of bio-inspired design. Various design functionalities were summarized based on the available resources from the AskNature database, then the main information extracted from the database, and they were labelled with corresponding multi-functionalities. Due to the high complexity of the multi-label classification system, multi-label classifiers were built based on different combinations of baseline classifiers and trained to classify selected AskNature pages. One case study was conducted to verify the impact of the proposed system. The results showed that the proposed system is feasible and would be a solution for classifying the bio-inspired design and functional basis knowledge extraction method to support DID methodology.

关键词： Domain Integrated Design Methodology natural language processing Text Mining Multi-label Classification System

来源：评论

学校读者我要写书评

暂无评论

Applying Data Science to Real-Time Data Analysis Problems 1

Applying Data Science to Real-Time Data Analysis Problems

引用

1st IEEE international conference on Emerging Research in Computational Science, ICERCS 2023

作者： Jain, Narendra Kumar Kumar, P. Kishore Singh, Shweta Katyal, Ashu Srisainath, R. Karnik, Madhuri P. Vivekananda Global University Department of Civil Engineering Jaipur India Faculty of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350359756

Records technology uses facts, evaluation strategies, and equipment to derive insights and enable decision-making for enterprises, firms, and governments. The data technology aims to increase predictive fashions and gear, which may be applied to enhance the know-how of clients, markets, and products. information technological know-how may be applied to actual-time statistics evaluation to recognize and discover styles and trends and modify enterprise operations to act in reaction to the changing environment. Actual-time data analysis can offer an aggressive advantage over other evaluation methods, especially within consumer enjoy optimization. Facts scientists use predictive analytics, machine mastering, synthetic intelligence (AI), and natural language processing (NLP) to system and analyze vast statistics in real time. The technological know-how of records facilitates delivering all the facts and points together to tell selection-making and enhance methods. information technology can be utilized to benefit insights into purchaser behavior, marketplace dynamics, and how products perform in their respective marketplace segments. Information technology applications give enterprises a more profound knowledge of purchaser wishes, choices, and behaviors, which can be used to improve patron stories and optimize pricing, product bundles, or promotional offers. With the assistance of statistics technology in real-time, organizations can count on consumer behavior if they want to reply and act as a consequence. © 2023 IEEE.

关键词： Consumer behavior

来源：评论

学校读者我要写书评

暂无评论

Discourse System Construction in the Digital Age: Linguistic Shifts and New Communication Norms

Discourse System Construction in the Digital Age: Linguistic...

引用

Information Science and Education (ICISE-IE), international conference on

作者： Guihua Zhang Peng Sun Shandong University of Engineering and Vocational Technology Jinan China

ISBN: (数字)9798331506766

ISBN: (纸本)9798331506773

With the rapid development of information technology, the discourse system in the field of education is undergoing significant changes. Educational technology has not only changed the way teaching content is delivered, but also profoundly affected the language interaction between teachers and students. With the popularization of online learning platforms and virtual classrooms, traditional face-to-face communication has gradually been replaced by digital communication forms. This paper analyzes the discourse system in different teaching environments through natural language processing (NLP) technology, and combines the simulation experiment of the virtual classroom platform to explore how educational technology promotes or affects the construction of discourse system. Experimental data show that in information-based teaching, the frequency of interaction between teachers and students has increased significantly, the discourse structure has become more diversified, and the language style tends to be concise and interactive. The simulation analysis results show that the construction of discourse system in the context of informatization tends to be more in line with the needs of modern education and supports more efficient learning interaction and knowledge transfer.

关键词： Information science Educational technology Linguistics Information age Digital communication natural language processing Mathematical models Frequency diversity Optimization knowledge transfer

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Enabled Examination Feedback System

Machine Learning-Enabled Examination Feedback System

引用

Industrial Electronics: Developments & Applications (ICIDeA), IEEE international conference on-

作者： Prashanth Ragam Botcha Taraka Rutesha Sai Anshita Priyadarshini Mekatotti Nallamala Ojasvi Adigoppula Jahnavi Pavithra Danaveni School of Computer Science & Engineering VIT-AP UNIVERSITY Inavolu Amaravati Vijayawada AP Department of Computer Science & Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad Telangana

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

The project proposes an Examination Feedback System utilizing machine learning to automate the evaluation of subjective answers in educational assessments. The system will analyze student responses and classify them under a number of predefined topics while making sure that the feedback it generates is tailored and specific to the needs of the students. The primary goal is to ensure improved outcomes through enhanced information to students, where improvement is needed, while helping educators identify performance trends. The system is powered by DistilBERT, which is a transformer-based natural language processing model which is known for its efficiency and contextual knowledge. The proposed system differs from previous manual grading systems in that it offers data-driven information while addressing confidentiality issues with a computationally efficient design. Thus, the examination process becomes scalable, accurate, and data-driven in satisfying the demands of upstream education systems with very limited computational infrastructure.

关键词： Training Accuracy Computational modeling Scalability Machine learning Manuals Transformers Market research natural language processing Context modeling

来源：评论

学校读者我要写书评

暂无评论

ClusCSE: Clustering-Based Contrastive Learning of Sentence Embeddings 11

ClusCSE: Clustering-Based Contrastive Learning of Sentence E...

引用

11th Joint international Information Technology and Artificial Intelligence conference, ITAIC 2023

作者： Guo, Kaihui Xu, Wenhua Liu, Tianyang Ocean University of China Faculty of Information Science and Engineering Shandong China

ISBN: (纸本)9798350333664

We propose ClusCSE, an unsupervised sentence embedding framework. Contrastive learning has been widely researched for learning universal sentence embeddings in natural language processing. Contrastive methods typically apply well-designed transformations to raw sentences to construct positive pairs and combine different raw sentences to construct negative pairs. Following the usual paradigm of contrastive learning, unsup-SimCSE advanced state-of-the-art unsupervised sentence embeddings by taking dropout as the minimal data augmentation strategy. Considering the training objective, unsup-SimCSE expects to maximize the similarity of positive pairwise instances while minimize the similarity of negative pairwise instances. Indeed, even different raw sentences could be highly semantically similar. Thus, simply reducing the similarity of negative pairwise embeddings is impractical. Sentence embeddings learned by unsup-SimCSE may contain false knowledge of relationships of different sentences. To alleviate it, we introduce online clustering to unsup-SimCSE and thus propose ClusCSE. Instead of just comparing sentences, ClusCSE also enforces consistency between cluster assignments, which makes the embeddings aware of similar sentence groups. Our evaluations on semantic textual similarity tasks demonstrate that our proposed ClusCSE achieves superior performance compared to unsup-SimCSE with higher average Spearman' s correlation of 1.19% on BERT-base. © 2023 IEEE.

关键词： cluster assignment contrastive learning pretrained language models sentence embeddings

来源：评论

学校读者我要写书评

暂无评论

Apply Bert-based models and Domain knowledge for Automated Legal Question Answering tasks at ALQAC 2021 13

Apply Bert-based models and Domain knowledge for Automated L...

引用

13th international conference knowledge and Systems engineering, KSE 2021

作者： Tieu, Truong-Thinh Chau, Chieu-Nguyen Bui, Nguyen-Minh-Hoang Nguyen, Truong-Son Nguyen, Le-Minh University of Science Faculty of Information Technology Vietnam National University Ho Chi Minh city Viet Nam Japan Advanced Institute of Science and Technology Japan

ISBN: (纸本)9781665499750

With robust development in NLP (natural language processing) methods and Deep Learning, there are a variety of solutions to the problems in question answering systems that achieve extraordinary results. In this paper, we describe our approach using at the Automated Legal Question Answering Competition (ALQAC) 2021. In this competition, we achieved the first prize of all tasks with the scores of 88.07%, 71.02%, 69.89% in Task 1, Task 2 and Task 3 respectively. © 2021 IEEE.

关键词： natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Empowering Non-Technical Users: A Chatbot-Driven Approach to Database Management

Empowering Non-Technical Users: A Chatbot-Driven Approach to...

引用

international conference on engineering of Modern Electric Systems (EMES)

作者： Adelin Gruian Cornelia Aurora Győrödi Robert Ştefan Győrödi Faculty of Electrical Engineering and Information Technology University of Oradea Oradea România Department of Computers and Information Technology University of Oradea Oradea România

ISBN: (数字)9798331525774

ISBN: (纸本)9798331525781

Modern enterprise applications must provide efficient and user-friendly access to databases, even for users with limited technical expertise. Traditional database management often requires advanced SQL knowledge, creating dependencies on specialized personnel and increasing operational bottlenecks. To bridge this gap, the integration of natural language processing (NLP) models in database management introduces a new paradigm, allowing users to interact with databases conversationally. This paper explores the impact of AI-powered chatbots on database accessibility, focusing on a case study that utilizes a natural language model to generate SQL queries. By analyzing the benefits and limitations of this approach, the study highlights key advantages such as improved productivity, reduced reliance on IT teams, and enhanced error handling. The chatbot-driven system is evaluated in comparison to traditional SQL-driven workflows, demonstrating its potential to streamline data access while maintaining security and reliability.

关键词： Industries Structured Query language Adaptation models Scalability Large language models Decision making Organizations Syntactics Database systems Security

来源：评论

学校读者我要写书评

暂无评论

Predicting Revelation Periods of Verses of the Quran via Deep Learning

Predicting Revelation Periods of Verses of the Quran via Dee...

引用

IEEE international WIE conference on Electrical and Computer engineering (WIECON-ECE)

作者： Umme Hani Ahsanur Rahman Electrical and Computer Engineering (ECE) Department North South University Bashundhara Dhaka Bangladesh

ISBN: (数字)9798331535476

ISBN: (纸本)9798331535483

The revelation period of a verse of the Quran provides invaluable insights into the historical context of that verse, helps us understand the prophet's biography, and empowers Islamic scholars to decide about the applicability of certain laws and/or to interpret that verse. They mostly relied on traditional methods (such as the occurrence of certain words and phrases, topics discussed, historical references, etc.) to decide the revelation periods of verses of the Quran. With modern deep-learning-based natural language processing (NLP) techniques, learning more complex patterns is possible, which may help us achieve this goal better. To our knowledge, no such attempt has been made before. Here, we attempt to fill this gap by employing different variations of a deep learning model to classify verses of the Quran into Meccan/Medinan categories. We analyze and interpret our results to get interesting insights.

关键词： Deep learning Biographies Computational modeling Supervised learning Predictive models natural language processing

来源：评论

学校读者我要写书评

暂无评论

Automating Lexicon Generation: A Comprehensive Review of Alternative Approaches 27

Automating Lexicon Generation: A Comprehensive Review of Alt...

引用

27th international conference on knowledge Based and Intelligent Information and engineering Sytems, KES 2023

作者： Ghali, Julien Pierre Edmond Inuzuka, Nobuhiro Shima, Kosuke Moriyama, Koichi Mutoh, Atsuko Nagoya Institute of Technology Gokisocho Showa Ward Aichi Nagoya466-006 Japan

Lexicon-based approaches to Document Classification are widely used, but the manual construction of lexicons can be time-consuming and resource-intensive. In this paper, we propose methods for automating the generation of lexicons later used for Document Classification. We explored diverse methods for generating lexicons, including semantic matches, frequency-based approaches, machine learning algorithms, and large language model techniques. We, later, used these lexicons to classify documents based on their content. By comparing our different lexicons results on a same task, based on criteria such as scalability and the F1 score, we determine optimized use-case for those methods. We show that our automated approaches are effective and efficient, producing accurate classifications with minimal human intervention. Some approaches have the potential to streamline the document classification process, reducing the time and resources required for manual lexicon generation, it also gives optimized use-case for the different methods. Thereafter, we discussed the obtained results. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： document classification lexicon generation machine learning natural language processing (NLP) semantic topic modeling transformers

来源：评论

学校读者我要写书评

暂无评论

Ten Years of Living Machines conferences: Transformers-Based Automated Topic Grouping 1

引用

11th international conference on Biomimetic and Biohybrid Systems (Living Machines)

作者： Carniel, Theophile Cazenille, Leo Dalle, Jean-Michel Halloy, Jose Univ Paris Cite CNRS LIED UMR 8236 F-75006 Paris France Agoranov Paris France Sorbonne Univ Paris France Ecole Polytech Palaiseau France

ISBN: (数字)9783031204708

ISBN: (纸本)9783031204692;9783031204708

The overwhelming growth in the number of scientific publications has its drawbacks: it is difficult to cope with it. Researchers need to constantly process the information contained in a very large and increasing number of articles to be up-to-date with their research community. This is especially difficult when interdisciplinary research requires knowledge of the state of the art in different fields. High interdisciplinarity is at the heart of the Living Machines conferences, which bring together scientists from different fields of biology, neuroscience, physics, robotics, artificial intelligence and other engineering fields. Here, using algorithmic AI methods, we analyze the publications of the ten "Living Machines" conferences to automatically discover clusters of research topics. We show that neural networks for natural language processing can find a set of thematic clusters that correspond to different research topics within this community.

关键词： Text mining Bibliography natural language processing Emerging topics BERT Transformers Clustering

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446页 << < 85 86 87 88 89 90 91 92 93 94 > >>

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：