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

26,472 篇 会议
406 册 图书
372 篇 期刊文献
3 篇 学位论文
1 篇 资讯

馆藏范围

27,254 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

16,535 篇 工学
- 15,143 篇 计算机科学与技术...
- 11,278 篇 软件工程
- 2,836 篇 信息与通信工程
- 1,806 篇 控制科学与工程
- 1,581 篇 电气工程
- 1,410 篇 生物工程
- 625 篇 生物医学工程（可授...
- 614 篇 化学工程与技术
- 576 篇 机械工程
- 523 篇 电子科学与技术（可...
- 508 篇 网络空间安全
- 397 篇 仪器科学与技术
- 371 篇 光学工程
- 280 篇 安全科学与工程
- 250 篇 交通运输工程
5,110 篇 理学
- 2,102 篇 数学
- 1,481 篇 物理学
- 1,469 篇 生物学
- 784 篇 统计学（可授理学、...
- 620 篇 系统科学
- 617 篇 化学
4,728 篇 管理学
- 3,171 篇 图书情报与档案管...
- 1,833 篇 管理科学与工程(可...
- 769 篇 工商管理
848 篇 医学
- 610 篇 临床医学
- 569 篇 基础医学(可授医学...
- 403 篇 公共卫生与预防医...
681 篇 法学
- 599 篇 社会学
573 篇 文学
- 401 篇 外国语言文学
451 篇 教育学
- 440 篇 教育学
252 篇 经济学
177 篇 农学
19 篇 艺术学
17 篇 军事学
1 篇 哲学

主题

5,711 篇 natural language...
1,715 篇 natural language...
1,552 篇 semantics
1,445 篇 natural language...
1,206 篇 machine learning
1,200 篇 sentiment analys...
1,152 篇 deep learning
978 篇 accuracy
917 篇 training
809 篇 data mining
796 篇 feature extracti...
795 篇 computational mo...
776 篇 artificial intel...
543 篇 knowledge engine...
526 篇 speech recogniti...
514 篇 large language m...
513 篇 transformers
492 篇 data models
466 篇 information retr...
463 篇 support vector m...

机构

58 篇 chitkara univers...
51 篇 lovely professio...
49 篇 school of comput...
33 篇 university of ch...
31 篇 school of comput...
31 篇 centre of interd...
31 篇 xi'an university...
30 篇 school of comput...
28 篇 tsinghua univers...
28 篇 school of comput...
27 篇 school of inform...
26 篇 zhejiang univers...
26 篇 microsoft resear...
24 篇 institute of inf...
24 篇 school of comput...
23 篇 school of inform...
22 篇 department of co...
22 篇 beijing univ pos...
21 篇 college of compu...
21 篇 school of inform...

作者

29 篇 liu yang
27 篇 wan wanggen
20 篇 tiejun zhao
18 篇 zhou guodong
18 篇 wang lei
16 篇 zhang tao
16 篇 zhao hai
16 篇 yang yang
15 篇 sabetzadeh mehrd...
15 篇 lei li
15 篇 liu ying
14 篇 li sheng
14 篇 wu jin
14 篇 zhang lei
14 篇 liu jun
13 篇 li yang
13 篇 li li
13 篇 shanmugasundaram...
13 篇 f. ren
12 篇 li peng

语言

26,244 篇 英文
910 篇 其他
150 篇 中文
5 篇 土耳其文
2 篇 西班牙文
1 篇 法文
1 篇 葡萄牙文

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

共 27256 条记录，以下是161-170 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：

Enhancing Small Model Performance in Educational Classification Tasks through knowledge Distillation

Enhancing Small Model Performance in Educational Classificat...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Xu, Haoxin Qi, Changyong Jiang, Bingqian Liu, Tong Zheng, Longwei Gu, Xiaoqing Shanghai Institute of AI for Education East China Normal University Shanghai China Department of Education Information Technology East China Normal University Shanghai China The School of Journalism and Communication Shanghai International Studies University Shanghai China School of Education City University of Macau China State Key Laboratory of Cognitive Intelligence Hefei China

ISBN: (纸本)9798350368741

As the demand for precision, efficiency, and low-cost solutions in educational classification tasks continues to grow, enhancing model performance has become a critical focus of research. While large language models excel in these tasks, their high cost and resource requirements limit widespread application. This study proposes a knowledge-Enhanced Distillation (KED) method, utilizing ChatGPT-4, ChatGPT-4o, and Llama3 as teacher models, and three different sizes of BERT models as student models. The method was validated across three real-world educational datasets. The results demonstrate that the KED method significantly improves the accuracy and F1 scores of small models in educational text classification tasks, while also substantially reducing computational costs and resource consumption. Notably, the KED method shows exceptional performance in scenarios involving few-shot learning and class imbalance. The innovation of this study lies in applying the KED method to educational classification tasks, filling a gap in current research and highlighting its significant potential for practical application in educational contexts. © 2025 IEEE.

关键词： Educational Application Few-Shot Learning knowledge Distillation Large language Model

来源：评论

学校读者我要写书评

暂无评论

Automated Framework for Constructing knowledge Graphs Oriented for Standard Analysis Using Large language Models 24

Automated Framework for Constructing Knowledge Graphs Orient...

引用

2nd international conference on Electronics, Computers and Communication Technology, CECCT 2024

作者： Zhu, Sitong Xia, Baobing Duan, Fangwei Zhao, Zhenyang Zhao, Zhenxia Xiao, Teliang Liu, Zhicheng Liu, Xia State Grid Liaoning Electric Power Co. LTD. Electric power Research Institute Liaoning Shenyang China Beijing State Grid Communication Accenture Information Technology Co. Ltd. Beijing China

ISBN: (纸本)9798400710193

In an era characterized by rapid technological growth and digital transformation, the necessity for efficient and structured knowledge representation has grown more crucial. Standards serve as fundamental cornerstones that offer guidelines, specifications, and frameworks to ensure the quality and interoperability of products, services, as well as systems. Nonetheless, the complexity and extensive nature of standard documents present significant challenges in extraction, alignment, and organization. Traditional manual processing methods frequently prove labor-intensive and susceptible to errors, impeding the capturing of intricate relationships and hierarchies within these standards. knowledge Graphs (KGs) provide a robust methodology for organizing information, facilitating improved functionalities for advanced search, reasoning, and analytics. Despite their potential, structuring KGs from standard documents continues to be challenging because of unstructured text, domain-specific terminology, and the intricacies in accurate information extraction. Recent advancements in natural language processing (NLP), particularly the emergence of Large language Models (LLMs) like GPT-3, have opened new avenues for automating the extraction and structuring of information from unstructured content. These models exhibit exceptional proficiency in comprehending and producing human-like text, positioning them as feasible solutions for addressing the complexities associated with standard documents. This paper presents an automated framework named StandardKG Builder, which utilizes LLMs to construct knowledge graphs tailored for standard analysis from multiple perspectives for complex information extraction. Our evaluation on a comprehensive dataset of standard documents highlights the framework’s effectiveness and scalability. By merging sophisticated knowledge representation with advanced NLP techniques, our work significantly enhances the accessibility and analysis of standard docu

关键词： knowledge graph

来源：评论

学校读者我要写书评

暂无评论

A Preliminary Work on Tenyidie Stemming Corpus Creation and Deep Learning Applications 4th

A Preliminary Work on Tenyidie Stemming Corpus Creation and...

引用

4th international conference on Emerging Trends and Technologies on Intelligent Systems, ETTIS 2024

作者： Angami, Teisovi Tuithung, Themrichon Department of Computer Science and Engineering National Institute of Technology Nagaland Dimapur India Department of Information Technology School of Engineering and Technology Nagaland University Lumami India

ISBN: (纸本)9789819757022

Tenyidie language belonging to the Tibeto-Burman family is one of the major languages of Nagaland in northeastern India. It is a low-resource, tonal, SOV, and a high agglutinative language. Stemming is an important natural language processing (NLP) task wherein the stem or the root word is identified and extracted. To the best of the authors knowledge, there has been no work reported on corpus creation and stemming using deep learning for the Tenyidie language. In this paper, we build an annotated corpus of 5400 manually stemmed words in Tenyidie to apply deep learning to the stemming task. We applied state-of-the-art deep learning models, such as the Encoder-decoder models, and compared our results with the rule-based approach, which uses both affix stripping and root word matching methods. Our experimental result shows that the deep learning models outperform the rule-based approach. We achieved the highest accuracy of 85.55% with Encoder-decoder (BLSTM) with attention. We also provide an analysis of the overstemmed and understemmed words in our test dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Contextual Analysis Based on Information Retrieval: Technical Analysis of Chinese and English Cross-language Q&A System 14th

Contextual Analysis Based on Information Retrieval: Technica...

引用

14th international conference on Frontier Computing, FC 2024

作者： Zhou, Jian School of Education and Foreign Languages Wuhan Donghu University Hubei Wuhan430212 China

ISBN: (纸本)9789819623907

Currently, the surge in Internet users across the globe has led to a surge in the linguistic diversity of online information resources. In this vast information environment, cross-lingual information retrieval has become a central theme in academic research. At the same time, automated Q&A technology is at the forefront of natural language processing, providing intelligent and progressive solutions for information retrieval. In the field of Q&A information retrieval, the operation of the system consists of three key stages: in-depth examination of the question, followed by comprehensive information exploration, and finally the refinement of key information through answers. The research focuses on the knowledge search of different language Q&A, aiming to remove language barriers for users and promote seamless multilingual communication. The system is designed to meet the challenges posed by the information explosion and is committed to providing users with efficient information extraction tools to improve search performance in complex multilingual environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Question answering

来源：评论

学校读者我要写书评

暂无评论

Cross-language Code Matching with IR2Vec and Cross-Entropy Loss 24

Cross-Language Code Matching with IR2Vec and Cross-Entropy L...

引用

8th international conference on natural language processing and Information Retrieval, NLPIR 2024

作者： Ghosh, Sagarika Das, Soma Chatterji, Sanjay Pratihar, Sanjoy CSE Indian Institute of Information Technology Kalyani West Bengal Kalyani India CSE University of Engineering and Management Jaipur Rajasthan Jaipur India CSE Institute of Engineering and Management Kolkata West Bengal Kolkata India

ISBN: (纸本)9798400717383

In contemporary software development and maintenance, the practice of reusing or copy-pasting code is prevalent to expedite processes. Consequently, numerous techniques have been developed to detect, compare, or match similar code within the same programming language. However, there remains a need for methods capable of detecting, comparing, or matching similar code across different programming languages. This paper presents a neural model utilizing IR2Vec embeddings and cross-entropy loss to facilitate the matching of similar code between disparate languages, such as C and C++. The proposed model achieves a matching accuracy of . To evaluate the model's efficacy, we compute Precision, Recall, and F1 score across various threshold values. © 2024 Copyright held by the owner/author(s).

关键词： Software design

来源：评论

学校读者我要写书评

暂无评论

Research on the Application of Intelligent Writing Teaching System Based on Computer Vision and natural language processing in Higher Vocational English 24

Research on the Application of Intelligent Writing Teaching ...

引用

5th international conference on Computer Science and Management Technology, ICCSMT 2024

作者： Wen, Liuchun Guangdong Polytechnic of Water Resources and Electric Engineering Guangdong Guangzhou China

ISBN: (纸本)9798400709999

In the context of vocational English teaching, writing skills are crucial for students' professional communication ***, traditional teaching methods often face challenges such as delayed feedback and insufficient *** the development of artificial intelligence technologies, the integration of computer vision (CV) and natural language processing (NLP) into writing education provides a novel solution to these *** study explores the application of a CV- and NLP-based intelligent writing assistance system in vocational English writing *** system enhances grammar correction, semantic understanding, and automated feedback, significantly improving students' writing performance while reducing teachers' *** experimental evaluation demonstrated that the system effectively improved writing accuracy, logical clarity, and overall learning *** findings indicate that AI-driven educational tools have great potential in transforming traditional language teaching practices. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Apprentices

来源：评论

学校读者我要写书评

暂无评论

knowledge Graph Entity Typing with Curriculum Contrastive Learning 31

Knowledge Graph Entity Typing with Curriculum Contrastive Le...

引用

31st international conference on Computational Linguistics, COLING 2025

作者： Wang, Hao Nuo, Minghua Jiang, Shan College of Computer Science Inner Mongolia University Inner Mongolia Hohhot010021 China National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Hohhot010021 China Inner Mongolia Key Laboratory of Multilingual Artificial Intelligence Technology Inner Mongolia Hohhot010021 China

ISBN: (纸本)9798891761964

The knowledge Graph Entity Typing (KGET) task aims to predict missing type annotations for entities in knowledge graphs. Most recent studies only focus on the structural information from an entity's neighborhood or semantic information from textual representations of entities or relations. In this paper, inspired by curriculum learning and contrastive learning, we propose the CCLET model using the Curriculum Contrastive Learning strategy for KGET, which uses the Pre-trained language Model (PLM) and the graph model to fuse the entity related semantic and the structural information of the knowledge Graph (KG) respectively. Our CCLET model consists of two main parts. In the knowledge Fusion part, we design an Enhanced-MLP architecture to fuse the text of the entity's description, related triplet and tuples;In the Curriculum Contrastive Learning part, we define the difficulty of the training course by controlling the level of added noise, we aim to accurately learn with curriculum contrastive learning strategy from easy to difficult. Our extensive experiments demonstrate that the CCLET model outperforms recent state-of-the-art models, verifying its effectiveness in the KGET task. © 2025 Association for Computational Linguistics.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Leveraging Information Retrieval Pipelines for Inventive Design: Application in Efficient Lattice Structures Manufacturing 24th

Leveraging Information Retrieval Pipelines for Inventive Des...

引用

24th international TRIZ Future conference

作者： Ayaou, Iliass Chibane, Hicham Koch, Simon Cavallucci, Denis INSA Strasbourg ICube CSIP Strasbourg France

ISBN: (纸本)9783031759253;9783031759239;9783031759222

In the contemporary landscape of technological advancement, artificial intelligence (AI) holds immense potential to address complex issues. This study aims at exploring AI's applicability in the initial stages of inventive design processes, specifically focusing on the initial situation analysis and resolution phases. It emphasizes leveraging information retrieval techniques, for the efficient design of innovative lattice structures, a noteworthy industrial challenge encompassing mass production at low cost. The approach entails formulating a TRIZ based contradiction query in natural language and implementing an intricate information retrieval pipeline using a meticulously analyzing vast patent databases, as they epitomize a significant knowledge pool in the realm of technological innovations. This research underscores the nuanced challenges associated with optimizing retrieval pipelines to ensure reliable and contextually relevant data extraction. Ultimately culminating in the development of novel lattice structures, our findings accentuate new horizons in industrial production.

关键词： Inventive Design Artificial intelligence Information retrieval natural language processing TRIZ Lattice structures 3D print

来源：评论

学校读者我要写书评

暂无评论

Frequency-Space Margin Perception for Open Set knowledge Distillation

Frequency-Space Margin Perception for Open Set Knowledge Dis...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Liu, Lijun Jing, Lihua Wang, Rui Wang, Yuan Wang, Zhishen Institute of Information Engineering CAS Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Department of Electronic Engineering Tsinghua University Beijing China

ISBN: (纸本)9798350368741

knowledge Distillation (KD) has attracted considerable attention as a typical model compression and knowledge transfer paradigm. However, most KD approaches are predicated on the implicit assumption: the deployed student model will exclusively encounter classes that have been seen during training, which goes against most real-world scenarios with unseen classes. To this end, we formalize the open-set KD task, where known classes are visible during training and unseen open-set classes appear when testing. We analyze the potential challenges of open-set KD from the discriminability of embedding space and the semantic separability of label space. Then we propose a Frequency-Spatial Margin Perception (FSMP) framework composed of a frequency-spatial feature distillation paradigm and a semantic margin-based calibration strategy. Experiments on multiple benchmarks demonstrate that FSMP consistently improves both the closed-set and open-set performance of existing KD methods across homogeneous and heterogeneous frameworks. © 2025 IEEE.

关键词： knowledge distillation Open-set recognition

来源：评论

学校读者我要写书评

暂无评论

HyPRETo: Hybrid Pre-trained Ontology Approach for Contextual Relation Classification on Mosquito Vector Biocontrol Agents 8th

HyPRETo: Hybrid Pre-trained Ontology Approach for Contextual...

引用

8th IFIP TC 12 international conference on Computer, Communication and Signal processing, ICCCSP 2024

作者： Jeyakodi, G. Bala, P. Shanthi Department of Computer Science School of Engineering and Technology Pondicherry University Puducherry India

ISBN: (纸本)9783031736162

Pre-trained language Model facilitates contextual relation classification by capturing contextual information, addressing word ambiguity, encoding global sentence context, enabling transfer learning, handling out-of-vocabulary words, and improving performance with limited labelled data. Existing pre-training approaches suffer in size, bias, interpretability, generalization, and the lack of domain specificity. To address this, HyPRETo, the hybrid model that combines the strength of token replacement and dynamic masking is proposed to achieve upgraded performance to increase classification accuracy. The Mosquito Vector Biocontrol Agents data is used for implementing the model for a contextual relation classification task. HyPRETo uses ontology to provide structured knowledge. HyPRETo is pre-trained by ELECTRA and fine-tuned by RoBERTa models. Feedforward and softmax activation function is used for classification. The natural language processing technique and SQL database are used to develop an automated question-answering system. The HyPRETo was evaluated with state-of-art models and achieved 98.42% accuracy. As a contribution, the manually annotated input dataset on the mosquito vector control agent is prepared for the classification task. Subsequently, the enhanced model is developed. The interface for an automated question-answering system for mosquito vector biocontrol agents is developed to assist public health applications such as mosquito vector control, disease control, ecosystem management, environmental conservation, and so on. © IFIP international Federation for Information processing 2025.

关键词： Vectors

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 << < 13 14 15 16 17 18 19 20 21 22 > >>

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：