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

14,082 篇 会议
98 册 图书
64 篇 期刊文献
1 篇 资讯

馆藏范围

14,245 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

9,383 篇 工学
- 8,572 篇 计算机科学与技术...
- 6,863 篇 软件工程
- 1,927 篇 信息与通信工程
- 1,310 篇 控制科学与工程
- 1,209 篇 电气工程
- 906 篇 生物工程
- 418 篇 生物医学工程（可授...
- 417 篇 电子科学与技术（可...
- 413 篇 网络空间安全
- 307 篇 化学工程与技术
- 288 篇 仪器科学与技术
- 281 篇 机械工程
- 266 篇 光学工程
- 211 篇 安全科学与工程
- 196 篇 交通运输工程
3,131 篇 理学
- 1,227 篇 数学
- 932 篇 生物学
- 887 篇 物理学
- 486 篇 统计学（可授理学、...
- 460 篇 系统科学
- 355 篇 化学
2,812 篇 管理学
- 1,831 篇 图书情报与档案管...
- 1,191 篇 管理科学与工程(可...
- 463 篇 工商管理
567 篇 医学
- 408 篇 临床医学
- 365 篇 基础医学(可授医学...
- 312 篇 公共卫生与预防医...
- 163 篇 药学(可授医学、理...
450 篇 法学
- 418 篇 社会学
217 篇 教育学
- 213 篇 教育学
194 篇 文学
155 篇 经济学
98 篇 农学
11 篇 艺术学
9 篇 军事学
1 篇 哲学

主题

2,893 篇 natural language...
873 篇 natural language...
822 篇 natural language...
817 篇 semantics
552 篇 deep learning
537 篇 machine learning
514 篇 sentiment analys...
508 篇 data mining
390 篇 knowledge engine...
360 篇 computational mo...
358 篇 training
356 篇 large language m...
315 篇 speech recogniti...
310 篇 feature extracti...
302 篇 speech processin...
272 篇 signal processin...
261 篇 accuracy
239 篇 neural networks
235 篇 knowledge based ...
234 篇 transformers

机构

55 篇 institute of inf...
50 篇 school of cyber ...
50 篇 school of commun...
40 篇 maharishi school...
38 篇 chitkara univers...
35 篇 lovely professio...
34 篇 university of ch...
34 篇 school of comput...
32 篇 school of comput...
31 篇 xi'an university...
30 篇 faculty of engin...
27 篇 department of el...
23 篇 school of inform...
22 篇 school of comput...
22 篇 department of co...
20 篇 centre of interd...
20 篇 beijing universi...
18 篇 pune
17 篇 zhejiang univers...
17 篇 college of compu...

作者

38 篇 ren fuji
27 篇 wan wanggen
17 篇 liu yang
16 篇 yixin zhong
14 篇 wu jin
14 篇 lei li
14 篇 shingo kuroiwa
13 篇 zhang tao
13 篇 wang lei
13 篇 sabetzadeh mehrd...
13 篇 zheng dequan
13 篇 liu jie
12 篇 tiejun zhao
12 篇 f. ren
11 篇 li sheng
11 篇 yang yang
11 篇 tao zhang
11 篇 li ying
11 篇 arora chetan
11 篇 wang wei

语言

11,805 篇 英文
2,409 篇 其他
49 篇 中文
3 篇 土耳其文

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

共 14245 条记录，以下是251-260 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：

Program Synthesis and natural language processing: A Systematic Literature Review 11

Program Synthesis and Natural Language Processing: A Systema...

引用

11th international conference in Software engineering Research and Innovation (CONISOFT)

作者： Ramirez-Rueda, Rolando Benitez-Guerrero, Edgard Mezura-Godoy, Carmen Barcenas, Everardo Univ Veracruzana Fac Estadist & Informat Xalapa Mexico Univ Nacl Autonoma Mexico Fac Ingn Mexico City Mexico

ISBN: (纸本)9798350328837;9798350328844

Program Synthesis is the process of automatically generating software from a requirement specification. This paper presents a systematic literature review focused on program synthesis from specifications expressed in natural language. The study aims to examine recent works published within the last five years, identifying emerging trends and potential areas for further exploration. Four major data sources (ieee, ACM, Springer, and Elsevier) were selected to gather a total of eight papers from various journals and conference proceedings. These papers propose solutions that target end-users or inexperienced programmers by leveraging natural language queries as inputs and generating expressions in boolean logic, DSL, or Java. The methods employed for program synthesis range from rule-based approaches that encode explicit translation rules from natural language to code, to more advanced techniques that learn these rules from input-output pairs.

关键词： Program Synthesis natural language processing

来源：评论

学校读者我要写书评

暂无评论

natural language processing in Strategic Planning Analysis 2

Natural Language Processing in Strategic Planning Analysis

引用

2nd international conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Shetty, Keerthi Tyagi, Swati Jha, Anupama Rao, D N Murali Krishna Arunkumar, J.R. Lakshmikanth, R. Nmam Institute of Technology Department of Mca Udupi India University of Delaware DE United States Vivekananda Institute of Professional Studies Guru Gobind Singh Ip University Vsit Delhi India Jntuh Electrical and Electronics Engineering India Modern Institute of Technology and Research Centre Department of Computer Science and Engineering Rajasthan Alwar India Adithya Institute of Technology Department of Management Studies Coimbatore India

ISBN: (纸本)9798350364699

natural language processing (NLP) has emerged as a game-changing technique in the field of strategic planning analysis. This development represents a significant step forward. Improved methods for obtaining meaningful insights from massive amounts of textual data are made available by natural language processing (NLP). According to the findings of this research project, the application of natural language processing (NLP) technology to enhance the strategic planning processes that are carried out within enterprises is being investigated. natural language processing (NLP) approaches, such as semantic analysis, sentiment identification, and topic modeling, can be utilized to acquire a more in-depth grasp of market tendencies, consumer feedback, and internal communications. This can be accomplished by utilizing these techniques. The study demonstrates how natural language processing (NLP) can facilitate the discovery of emergent patterns, simplify the understanding of data, and encourage decision-making that is driven by data. There are a great number of case studies that demonstrate the incorporation of natural language processing (NLP) into strategic frameworks. These case studies show improvements in the accuracy of forecasting, risk management, and competitive analysis processes. The findings of this study demonstrate the potential for natural language processing (NLP) to revolutionize strategic planning by providing a more nuanced and comprehensive evaluation of qualitative data. This, in turn, will ultimately result in strategic decisions that are more informed and agile. © 2024 ieee.

关键词： Risk management

来源：评论

学校读者我要写书评

暂无评论

LLM4Workflow: An LLM-based Automated Workflow Model Generation Tool 24

LLM4Workflow: An LLM-based Automated Workflow Model Generati...

引用

39th ACM/ieee international conference on Automated Software engineering (ASE)

作者： Xu, Jia Du, Weilin Liu, Xiao Li, Xuejun Anhui Univ Anhui Prov Int Joint Res Ctr Adv Technol Med Imag Sch Comp Sci & Technol Hefei Peoples R China Anhui Univ Sch Internet Hefei Peoples R China Deakin Univ Sch Informat Technol Geelong Vic Australia

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

Workflows are pervasive in software systems where business processes and scientific methods are implemented as workflow models to achieve automated process execution. However, despite the benefit of no/low-code workflow automation, creating workflow models requires in-depth domain knowledge and non-trivial workflow modeling skills, which becomes a hurdle for the proliferation of workflow applications. Recently, Large language models (LLMs) have been widely applied in software code generation given their outstanding ability to understand complex instructions and generate accurate, context-aware code. Inspired by the success of LLMs in code generation, this paper aims to investigate how to use LLMs to automate workflow model generation. We present LLM4Workflow, an LLM-based automated workflow model generation tool. Using workflow descriptions as the input, LLM4Workflow can automatically embed relevant API knowledge and leverage LLM's powerful contextual learning abilities to generate correct and executable workflow models. Its effectiveness was validated through functional verification and simulation tests on a real-world workflow system. LLM4Workflow is open sourced at https://***/ISEC-AHU/LLM4Workflow, and the demo video is provided at https://***/XRQ0saKkuxY.

关键词： Automated Workflow Model Generation Large language Models Low Code Development

来源：评论

学校读者我要写书评

暂无评论

JOINT MULTI-FACTS REASONING NETWORK FOR COMPLEX TEMPORAL QUESTION ANSWERING OVER knowledge GRAPH 49

JOINT MULTI-FACTS REASONING NETWORK FOR COMPLEX TEMPORAL QUE...

引用

49th ieee international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Huang, Rikui Wei, Wei Quo, Xiaoye Xie, Wenfeng Mao, Xianling Chen, Dangyang Huazhong Univ Sci & Technol Inst Artificial Intelligence Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Hubei Peoples R China Ping An Property & Casualty Insurance Co China Lt Shenzhen Peoples R China Beijing Inst Technol Sch Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Temporal knowledge Graph (TKG) is an extension of regular knowledge graph by attaching the time scope. Existing temporal knowledge graph question answering (TKGQA) models solely approach simple questions, owing to the prior assumption that each question only contains a single temporal fact with explicit/implicit temporal constraints. Hence, they perform poorly on questions which own multiple temporal facts. In this paper, we propose Joint Multi Facts Reasoning Network (JMFRN), to jointly reasoning multiple temporal facts for accurately answering complex temporal questions. Specifically, JMFRN first retrieves question-related temporal facts from TKG for each entity of the given complex question. For joint reasoning, we design two different attention (i.e., entity-aware and time-aware) modules, which are suitable for universal settings, to aggregate entities and timestamps information of retrieved facts. Moreover, to filter incorrect type answers, we introduce an additional answer type discrimination task. Extensive experiments demonstrate our proposed method significantly outperforms the state-of-art on the well-known complex temporal question benchmark TimeQuestions.

关键词： Temporal knowledge graph question answering knowledge graph neural language processing

来源：评论

学校读者我要写书评

暂无评论

Enhancing Hindi Named Entity Recognition through Ensemble Learning 10

Enhancing Hindi Named Entity Recognition through Ensemble Le...

引用

10th ieee Uttar Pradesh Section international conference on Electrical, Electronics and Computer engineering, UPCON 2023

作者： Singh, Aayushi Singh, Sumit Tiwary, Uma Shanker Iiit Allahabad Information Technology Prayagraj India

ISBN: (纸本)9798350382471

The main goal of the NER task, a well-known research field, is to identify people, groups, places, and other business entities in text. This task entails classifying and recognising these named things, which is essential for many applications of natural language processing. In this study, we used ensemble approaches to improve the NER task performance. We enhanced outcomes in terms of accuracy, precision, and recall by merging numerous models and their predictions. The ensemble approach offered a stronger and more dependable solution for named entity recognition by successfully addressing the shortcomings of individual models. The outcomes of the experiment showed how the ensemble technique could improve the NER task's overall performance. © 2023 ieee.

关键词： Cross entropy Ensemble learning knowledge-base Named Entity Recognition natural language processing Transformer

来源：评论

学校读者我要写书评

暂无评论

knowledge engineering Using natural language processing of User Reviews for Bahrain's Mobile Government Applications

Knowledge Engineering Using Natural Language Processing of U...

引用

2023 ieee international conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023

作者： Salman, Hussain Almohsen, Eman Aljawder, Maan Althawadi, Ali University of Bahrain Sakhir College of Applied Studies Bahrain University of Bahrain Sakhir College of It Bahrain

ISBN: (纸本)9798350313635

The Kingdom of Bahrain has launched various mobile government applications that work side by side with the national e-government portal by providing a range of government services, while services offered on mobile applications are still limited compared to the e-government portal, utilization of end users' feedback is vital to improve and enhance functionality to ensure proper digital integration on the mobile environment. In this research, knowledge engineering using natural language processing is implemented to analyze 20,000 user reviews of the top four most reviewed google play mobile government applications in Bahrain. Two resampling techniques were used to under-sample and over-sample unbalanced datasets;Near-Miss and Synthetic Minority Oversampling combined with Edited Nearest Neighbor. The performance of three classifiers for data analysis was compared and assessed before and after data resampling. Results suggest that the Random Forest classifier outperformed Artificial Neural Network and LogitBoost. © 2023 ieee.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

TELLMe: Teaching and Exploiting Large language Models for Model Selection in Text Retrieval

TELLMe: Teaching and Exploiting Large Language Models for Mo...

引用

international Joint conference on Neural Networks (IJCNN)

作者： Li, Zhenzi Bai, Jun Chen, Zhuofan Li, Chen Ouyang, Yuanxin Rong, Wenge Beihang Univ State Key Lab Complex & Crit Software Environm Beijing Peoples R China

ISBN: (纸本)9798350359329;9798350359312

Text retrieval, a pivotal application in natural language processing (NLP), involves retrieving pertinent documents from a candidate pool for a certain query. Due to the outstanding performance and improved convergence, Pre-trained language Models (PLMs) are extensively employed in text retrieval. However, selecting the prime model from a multitude of PLMs remains a challenge, termed Model Selection (MS). In this paper, we address the MS by proposing a novel twostage approach, Teaching and Exploiting Large language Models (TELLMe). In the first stage, we efficiently retrieve models through Large language Models (LLMs) prompting, leveraging the unparalleled world knowledge of LLM, where In-Context Learning (ICL) and Chain-of-Thought (CoT) are incorporated to overcome the inherent challenges in LLMs' understanding of MS tasks. After retrieving potential high-performing models, the second stage employs Transferability Estimation (TE) for further model ranking. To tackle the issue of untrue hard labels faced by TE approaches, we propose a novel method, Evidence maximized from Soft labels (EaSe), which utilizes soft labels from LLM-encoded query embeddings and document embeddings to evaluate transferability scores. Our proposed approach combines the exceptional capabilities of LLMs and provides an efficient and generalized solution for MS regarding text retrieval. We further systematically evaluate the TELLMe framework on three diverse datasets, demonstrating its effectiveness and superiority.

关键词： Transferability Estimation Model Selection Text Retrieval Large language Model

来源：评论

学校读者我要写书评

暂无评论

Demo: CaseFinder: Automated Visual and Quantitative Analysis Tool for Police Narrative

Demo: CaseFinder: Automated Visual and Quantitative Analysis...

引用

9th ieee/ACM international conference on Connected Health - Applications, Systems and engineering Technologies (CHASE)

作者： Brown, Martin Thomas, Dominic Khan, Md Abdullah Al Hafiz Azmee, Abm Adnan Nandan, Monica Pei, Yong Kennesaw State Univ Dept Data Sci & Analyt Marietta GA USA Kennesaw State Univ Comp Sci Marietta GA USA Kennesaw State Univ Informat Syst Marietta GA USA Kennesaw State Univ Social Work & Human Serv Marietta GA USA

ISBN: (纸本)9798350345025;9798350345018

This demonstration introduces the CaseFinder tool, a GUI designed to automate visualizations and quantitatively analyze 911 police reports. The tool allows for efficient data exploration for non-technical users integrating behavioral health-related keywords. By amalgamating diverse keyword category inputs, CaseFinder provides a holistic approach to analyzing reports by uncovering indications of behavioral health problems while including perspectives from multiple professional domains. Ultimately, CaseFinder aims to improve the understanding of the magnitude of the problem of behavioral health issues involved in 911 crises to mitigate reoccurrence.

关键词： mental health behavioral health natural language processing

来源：评论

学校读者我要写书评

暂无评论

Quantum natural language processing Application for Estimating SQL Query Metrics 5

Quantum Natural Language Processing Application for Estimati...

引用

2024 international conference on Quantum Computing and engineering

作者： Uotila, Valter Univ Helsinki Helsinki Finland

ISBN: (纸本)9798331541378

Quantum natural language processing (QNLP) is built on a novel, category theoretical quantum machine learning model, which we use to solve a well-researched problem in the database field: estimating metrics for SQL queries. The metrics we focus on are latency (i.e., the execution time), cost (i.e., a value of how expensive the query is in total), and cardinality (i.e., the number of rows in the result table). The critical link between QNLP and the database problem lies in using grammars, such as context-free grammar. Both natural language and SQL queries admit grammatical presentations, which allow us to develop a comprehensive framework for applying QNLP methods to solve the query estimation problem. The model comprises an encoding mechanism and a training phase, integrating classical and quantum subroutines. The encoding mechanism transforms SQL queries into parametrized quantum circuits as in QNLP. Classical optimization algorithms optimize the circuit parameters during training to predict query metrics. Comparing our model to the QNLP models, our model achieves accuracy comparable to the QNLP model in binary classification tasks. Additionally, we expand upon previous research by implementing multi-class classification tasks and comparing the cardinality estimation results to those of state-of-the-art databases. Our theoretical analysis of the quantum machine learning model includes calculations of its expressibility and entangling capabilities. The analysis reveals that the model possesses beneficial properties, making it suitable to be executed on near-term quantum hardware.

关键词： quantum natural language processing quantum machine learning relational databases SQL grammars

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Survey of Event Extraction Methods in natural language processing 5

Comprehensive Survey of Event Extraction Methods in Natural ...

引用

5th international conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Kulkarni, Amit Dogra, Varun School of Computer Applications Lovely Professional University Punjab Phagwara144411 India School of Computer Science and Engineering Lovely Professional University Punjab Phagwara144411 India

ISBN: (纸本)9798331530013

Event Extraction (Event Extraction) plays an essential role in NLP (natural language processing) by automating the identification and extraction of events from unstructured textual data. This paper provides a comprehensive overview of event extraction, highlighting its significance in various domains such as security, law, and financial analysis. The paper categorizes event extraction into closed-domain and open-domain approaches. It also talks about various techniques like argument identification, event trigger identification, as well as event type classification. It explores methodologies including machine learning, pattern matching, & deep learning, emphasizing their application in different domains. Evaluation metrics to evaluate the effectiveness of EE systems are explored, including precision, recall, as well as the F1 score. Through a systematic review of the literature, the paper underscores the advancements, challenges, and future directions in EE, positioning it as a critical component in extracting actionable knowledge from textualsources. © 2024 ieee.

关键词： Deep learning

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 << < 22 23 24 25 26 27 28 29 30 31 > >>

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：