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

4,244 篇 会议
102 册 图书
50 篇 期刊文献

馆藏范围

4,396 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,559 篇 工学
- 2,414 篇 计算机科学与技术...
- 1,799 篇 软件工程
- 346 篇 信息与通信工程
- 274 篇 控制科学与工程
- 258 篇 电气工程
- 173 篇 生物工程
- 93 篇 化学工程与技术
- 78 篇 生物医学工程（可授...
- 72 篇 机械工程
- 66 篇 网络空间安全
- 60 篇 电子科学与技术（可...
- 49 篇 仪器科学与技术
- 36 篇 光学工程
- 32 篇 材料科学与工程（可...
- 30 篇 动力工程及工程热...
- 29 篇 安全科学与工程
791 篇 管理学
- 542 篇 图书情报与档案管...
- 300 篇 管理科学与工程(可...
- 104 篇 工商管理
675 篇 理学
- 303 篇 数学
- 178 篇 生物学
- 156 篇 物理学
- 118 篇 统计学（可授理学、...
- 100 篇 化学
- 68 篇 系统科学
91 篇 医学
- 72 篇 临床医学
- 64 篇 基础医学(可授医学...
- 48 篇 公共卫生与预防医...
75 篇 法学
- 68 篇 社会学
73 篇 教育学
- 72 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

1,052 篇 natural language...
318 篇 semantics
314 篇 natural language...
299 篇 natural language...
231 篇 knowledge engine...
226 篇 data mining
210 篇 machine learning
168 篇 information retr...
150 篇 training
146 篇 artificial intel...
144 篇 deep learning
141 篇 accuracy
133 篇 computational mo...
120 篇 knowledge based ...
119 篇 sentiment analys...
118 篇 ontologies
111 篇 computer science
110 篇 databases
109 篇 feature extracti...
108 篇 knowledge graph

机构

27 篇 faculty of engin...
26 篇 maharishi school...
22 篇 school of inform...
15 篇 centre of interd...
14 篇 lovely professio...
14 篇 institute of inf...
13 篇 school of comput...
13 篇 department of co...
13 篇 school of cyber ...
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

4,215 篇 英文
163 篇 其他
25 篇 中文

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

共 4396 条记录，以下是271-280 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：

Limitations of Large language Models 8

Limitations of Large Language Models

引用

8th IEEE international conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Sanu, Erin Amudaa, T. Keerthi Bhat, Prasiddha Dinesh, Guduru Chate, Apoorva Uday Kumar Ramakanth Kumar, P. Rv College of Engineering Bangalore India Rv College of Engineering Department Of Cse Bangalore India

ISBN: (纸本)9798331505462

Large language Models (LLMs) have become a cornerstone of modern natural language processing, exhibiting remarkable capabilities in diverse applications. However, these models are not flawless. This paper provides a comprehensive analysis of the loopholes inherent in LLMs, focusing on adversarial attacks, biases, hallucinations and outdatedness. One of the main problems is hallucinations, where models generate plausible but inaccurate or unreal information. Biases introduced into training data can lead to outcomes that reflect and amplify societal prejudices leading to discriminatory behavior. Adversarial attacks exploit vulnerabilities in machine learning models by introducing subtle perturbations to input data, causing the model to make incorrect predictions with high confidence. Additionally, LLMs considerably struggle when it comes to domain-specific queries as they lack specialized knowledge and have a generalized training, thus highlighting the need for domain-specific customization. By inspecting these vulnerabilities, we aim to highlight the critical areas that require attention to ensure the safe and effective deployment of LLMs. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Unlocking the Potential of Large language Models in Legal Discourse: Challenges, Solutions, and Future Directions 6

Unlocking the Potential of Large Language Models in Legal Di...

引用

6th international conference on Intelligent Computing in Data Sciences, ICDS 2024

作者： Kaoutar, M'Rhar Chaima, Ben Jaafar Omar, Bencharef Outmane, Bourkoukou Cadi Ayyad University Computer and System Engineering Laboratory FSTG Marrakesh Morocco

ISBN: (纸本)9798350351200

The rise of Large language Models (LLMs) has been remarkable, especially exemplified by the achievements of systems such as ChatGPT and Google's Bard. Both specialized and general users are warmly embracing these potent tools, indicating their increasing integration into everyday life. Nevertheless, challenges persist in their widespread adoption, particularly within specialized fields where they necessitate meticulous fine-Tuning and access to high-quality data. Additionally, their lack of interpretability further complicates matters, often relegating them to the status of 'black boxes'. Within the legal domain, LLMs harbor transformative potential but encounter obstacles due to legal hallucinations. This research delves into these hallucinations through a distinct set of legal queries pertaining to Canadian tax law, drawing comparisons between state-of-The-Art LLMs. Its objective is to illuminate their efficacy in legal discourse and specialized domains, capitalizing on their broad knowledge base. The research advocates for fine-Tuning as a potential solution, stressing the significance of domain-specific LLMs and delineating methods for their development. This includes considerations such as dataset curation, preprocessing techniques, model selection, and adherence to regulatory requirements, encompassing the creation of domain-specific vocabularies. Practical implementation entails the generation of domain-specific LLMs tailored for legal tasks such as research, information retrieval, and question answering. Despite inherent limitations, the study proposes avenues for enhancement and underscores the significance of LLMs utilization in legal services. This contributes to the evolution of natural language processing technology within the legal realm. © 2024 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

Research on Named Entity Recognition Algorithm Based on NLP 12

Research on Named Entity Recognition Algorithm Based on NLP

引用

12th IEEE international conference on Information and Communication Networks, ICICN 2024

作者： Qu, WangYue Li, JianLiang College of Information Engineering Northwest Agriculture and Forestry University Shaanxi Yangling China

ISBN: (纸本)9798350355802

In recent years, with the rapid development of natural language processing technology, Named Entity Recognition (NER), as one of the key tasks in the field of NLP, has attracted wide attention. NER plays an important role in knowledge graph construction, machine translation, question answering system and other downstream applications. This paper aims to investigate named entity recognition algorithms based on deep learning, and propose an improved lattice model method (SLBERT) and a new method based on Machine Reading Comprehension (MRC) (GFMRC) to improve the performance of NER. The experimental results demonstrate that our proposed method is effective and achieves state-of-the-art performance compared to other methods. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing engineering Document Analysis Through Structured Data Mapping

Enhancing Engineering Document Analysis Through Structured D...

引用

2024 Abu Dhabi international Petroleum Exhibition and conference, ADIPEC 2024

作者： Rascanu, G. Dzhusupova, R. Guo, Z. McDermott International Ltd. The Hague Netherlands

ISBN: (纸本)9781959025498

This paper presents an innovative approach for mapping engineering documents, particularly unstructured PDF files, to knowledge graphs, offering significant benefits for both engineering processes (i.e. such as 'review-check-approve' process) and AI-powered development. The method aims at improving efficiency, enhancing decision-making capabilities, reducing document turn-around duration, and thus decreasing costs while increasing productivity. Specific advantages include: • Quick overview for reviewers to prioritize tasks - more weight can be given to identified main topics with less time on the side topics. • Improved quality: interrupted relationships and isolated entities may indicate inconsistency that is usually overlooked in the traditional review process. • A faster review process achieved through common understanding between reviewers, resulting in a subjective time reduction (average 10% improvement) while enhancing quality. Our method leverages advanced natural language processing (NLP) techniques, sentence transformers and large language models (LLMs) to transform complex document content into structured knowledge visual representations. This approach addresses the challenge of efficiently extracting information from unstructured engineering documents by first identifying relevant keywords, that align with the main topics of the document, through a robust initial process. The extracted keywords define the framework upon which the entire knowledge graph is built, ensuring its relevance and utility. Central to our methodology are novel techniques in LLM-based prompt engineering that enhance entity and relationship extraction in complex engineering contexts. These techniques incorporate chain-of-thought reasoning for improved accuracy. Furthermore, we introduce a robust process of relevant keyword extraction as an initial step, which sets the foundation for all subsequent stages from entity extraction to final graph presentation. The resulting knowledge gra

关键词： knowledge graph

来源：评论

学校读者我要写书评

暂无评论

AI-Enhanced Pedagogy in Higher Education: Redefining Teaching-Learning Paradigms

AI-Enhanced Pedagogy in Higher Education: Redefining Teachin...

引用

2024 international conference on knowledge engineering and Communication Systems, ICKECS 2024

作者： Kakhkharova, Matlyuba Tuychieva, Sayyora International Islamic Academy of Uzbekistan Department of International Relations and Social Sciences Tashkent Uzbekistan

ISBN: (纸本)9798350359688

This paper delves into the transformative landscape of higher education through the lens of AI, introducing a paradigm shift in teaching and learning methodologies. The exploration of AI-enhanced pedagogy emerges as a pivotal response to the dynamic challenges faced by educational institutions, aiming to redefine conventional approaches. The core objective is to harness the potential of artificial intelligence in order to individualize and optimize the learning experience. By synthesizing advanced machine learning algorithms and intelligent systems, the proposed framework creates an adaptive learning environment tailored to the unique needs and preferences of each student. The paper conducts a thorough literature survey, unveiling gaps in current research, and positions the proposed work within the context of existing knowledge. The envisioned methodology involves the strategic integration of data collection, preprocessing, and algorithm selection, ensuring the efficacy of the AI-enhanced pedagogical model. The implementation model, discussed in detail, incorporates natural language processing, recommendation systems, and learning analytics to construct a scalable and customizable educational framework. The results, drawn from the implementation, showcase improvements in student performance, engagement, and satisfaction. In conclusion, this paper advocates for the widespread adoption of AI-enhanced pedagogy, emphasizing its potential to revolutionize higher education by providing a personalized and effective learning experience for students and educators alike. Future research directions and challenges are also contemplated, contributing to the ongoing discourse on the transformative role of AI in education. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

The Research and Construction of Practical Case Library of Database Based on knowledge Graph

The Research and Construction of Practical Case Library of D...

引用

2023 IEEE international conference on Control, Electronics and Computer Technology, ICCECT 2023

作者： Xiong, Shaojun Qi, Xiangtao Wuhan Business University School of Information Engineering Hubei Province Wuhan City China

ISBN: (纸本)9798350399028

Using database technology and AI, it is of great significance to explore the database case for data processing and analysis of the digital transformation platform based on knowledge graphe. knowledge graph includes knowledge engineering, natural language processing, database, machine learning. With the development of university-enterprise cooperation in china, high-quality resources in the computer industry will be introduced into the practice of database courses, so as to create new database practice case library with new engineering characteristics. Colleges and universities have realized the training goal of talent technology under the background of new engineering by building a hierarchical database oriented talent training mode. knowledge graph is used to process massive multi-dimensional data, which can be considered as a semantic network. The knowledge graph processing steps involve knowledge representation, knowledge acquisition, knowledge fusion, knowledge calculation and knowledge reasoning. The knowledge graph includes the processing and calculation of database data. Then, the construction of the case of the database can use the knowledge graph technology. The construction and reform of the database practice case for the new engineering and engineering education accreditation, and the strengthening of both theory and practice, have an obvious role and significance in improving the quality of talent training in the computer direction, promoting practical teaching and improving teaching quality. Based on the innovative mode of university-enterprise cooperation, this paper explores the path and direction of the construction of the case library for practical of database using knowledge graph. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Intent Classification of Nepali Factoid Questions

Intent Classification of Nepali Factoid Questions

引用

2023 international conference on Cognitive Computing and Complex Data, ICCD 2023

作者： Timilsina, Sushil Khadka, Ashim Lin, Jianchu Faculty of Science and Technology Gandaki College of Engineering and Science Pokhara Nepal Faculty of Science and Technology Nepal College of Information Technology Lalitpur Nepal Faculty of Computer and Software Engineer Huaiyin Institute of Technology Jiangsu China

ISBN: (纸本)9798350306293

Question Classification plays a vital role in identifying the accurate answer to any question, and is considered as a core component of Question Answering Systems. In Nepali natural language processing, the area of Question Answering has not even been initiated due to a lack of dataset. The dataset of Nepali factual questions has been created by collecting questions from general knowledge books and labelling them with developed taxonomy. The problem of Nepali factoid question classification has been studied with a Support Vector Machine, which works as a baseline classification algorithm and obtained a 0.74 weighted F1-score in the imbalance dataset. The experimental results of the proposed model show the effectiveness of the approach in classifying factoid questions accurately compared with the state-of-the-art approaches. © 2023 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

Upper Bound Analysis of TSN End-to-End Delay Based on Network Calculus 5

Upper Bound Analysis of TSN End-to-End Delay Based on Networ...

引用

5th international conference on natural language processing, ICNLP 2023

作者： Guo, Juan Wang, Huixiao Wang, Zexin Chang, Zhixian Xi'an University of Posts and Telecommunication Dept. School of Communication and Information Engineering Xi'an China

ISBN: (纸本)9798350302219

To analyze the upper bound of end-to-end delay in time-sensitive networks, an improved calculation model of end-to-end transmission delay based on network calculus is derived according to the relevant knowledge of deterministic network calculus. The effects of GCL gate opening time, scheduling period, the overlap of transmission Windows, and different priorities of traffic on the delay index were analyzed experimentally, and the end-to-end worst-case transmission delay of time triggered (TT) traffic in the whole process of traffic transmission was calculated. Finally, through comprehensive analysis of GCL and reasonable configuration of parameters, good transmission capacity of the communication network is ensured, which provides a theoretical basis for efficient deployment of the communication network and optimal allocation of network resources. © 2023 IEEE.

关键词： deterministic network calculus end-to-end delay gate control lists Time-sensitive networks

来源：评论

学校读者我要写书评

暂无评论

Leveraging natural language processing for Enhanced Maintenance Data in Power System Management 51

Leveraging Natural Language Processing for Enhanced Maintena...

引用

51st international conference on Computers and Industrial engineering, CIE 2024

作者： Payette, Mathieu Abdul-Nour, Georges Meango, Toualith Jean-Marc Diago, Miguel Côté, Alain Université du Québec à Trois-Rivières 3351 Bd des Forges Trois-RivièresQCG8Z-4M3 Canada Hydro-Québec 1800 Bd Lionel-Boulet VarennesQCJ3X-1S1 Canada

Maintenance is essential to ensure reliability and safety, especially in asset-intensive industry like power systems. Consequences of loss of electricity can be catastrophic for society, as demonstrated by the crisis in Texas in 2021, or the 1998 ice storm in Quebec. To maintain the grid while controlling costs, the reliability of network components must be thoroughly analyzed, relying heavily on years of collected maintenance data. This work proposes a method for classifying maintenance work in order to improve the quality of the data used to model the life cycle of assets. natural language processing (NLP) techniques, derived from artificial intelligence, include text classification tools that are ideal for this type of problem. However, analysis of maintenance texts requires that the NLP tools be adapted. Furthermore, another level of complexity is added, as the data analyzed are in French but contain plenty of anglicisms. This article compares the classification of maintenance orders using off-the-shelf tools with annotation tools adapted to the context of power systems. The results show a significant improvement in classification accuracy when pre-processing and annotation techniques are employed to refine and adapt technical texts. These findings support the literature on domain-specific applications of NLP, which emphasizes the importance of including domain knowledge into pre-trained models. This study offers crucial information for professionals, especially within the energy industry, where dependable historical data is essential for effective asset management. Furthermore, it highlights the necessity of intensive preprocessing and custom annotation when using state-of-the-art NLP algorithms in real industrial cases. © 2024 Computers and Industrial engineering. All rights reserved.

关键词： Asset management

来源：评论

学校读者我要写书评

暂无评论

SeerahGPT: Retrieval Augmented Generation based Large language Model 18

SeerahGPT: Retrieval Augmented Generation based Large Langua...

引用

18th international conference on Open Source Systems and Technologies, ICOSST 2024

作者： Obaid, Surayya Bawany, Narmeen Zakaria Center for Computing Research Department of Computer Science and Software Engineering Jinnah Univesity for Women Karachi Pakistan

ISBN: (纸本)9798331508692

Large language Models(LLMs) have become widely recognized in recent years for their exceptional performance in language generation capabilities. As a result, an unprecedented rise is seen in its use cases in various domains specifically involving natural language processing(NLP). These models however perform suboptimally when exploited in the field of studies where authenticity of the generated content is a critical aspect. One such domain is usage of LLM for exploration of the life of Prophet Muhammad S.A.W(commonly referred to as Seerah). It is of utmost significance to ensure the authenticity and reliability in the sources used and reported by the LLM due to the sensitive nature of the domain. The contemporary LLMs, however, lack the explainability in their response due to their inherent black-box nature. In our study, we have presented a novel LLM named SeerahGPT that addresses this challenge with the help of retrieval-augmented generation (RAG). This technique enables the model to utilize both parametric and nonparametric memories for generating response of queries. Our model, built on the Llama-2-7b architecture, employs Sentence Transformer embedding to effectively retrieve relevant information. The model's capabilities are augmented by integrating it with a corpus having Islamic texts such as the Quranic translation and Hadith collections, and historical accounts. The model's performance is benchmarked against its base model using both quantitative and qualitative metrics. The comparative analysis with Llama-2-7b revealed that SeerahGPT incorporation with external knowledge sources, provided more authentic and verifiable responses, despite the others exhibiting greater fluency. Performance metrics such as BLEU, ROUGE, and METEOR indicated SeerahGPT's better accuracy and contextual handling. This study paves way for analysis of such sensitive domains in more efficient way that can be utilized in other complex domains such as Islamic theology and Fiqh or legal

关键词： natural language processing systems

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440页 << < 24 25 26 27 28 29 30 31 32 33 > >>

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：