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241-250 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 High-order Interaction Awareness in LLM-based Recommender Model

Enhancing High-order Interaction Awareness in LLM-based Reco...

引用

2024 conference on Empirical Methods in natural language processing, EMNLP 2024

作者： Wang, Xinfeng Cui, Jin Fukumoto, Fumiyo Suzuki, Yoshimi Graduate School of Engineering University of Yamanashi Kofu Japan Interdisciplinary Graduate School University of Yamanashi Kofu Japan

ISBN: (纸本)9798891761643

Large language models (LLMs) have demonstrated prominent reasoning capabilities in recommendation tasks by transforming them into text-generation tasks. However, existing approaches either disregard or ineffectively model the user-item high-order interactions. To this end, this paper presents an enhanced LLM-based recommender (ELMRec). We enhance whole-word embeddings to substantially enhance LLMs' interpretation of graph-constructed interactions for recommendations, without requiring graph pre-training. This finding may inspire endeavors to incorporate rich knowledge graphs into LLM-based recommenders via whole-word embedding. We also found that LLMs often recommend items based on users' earlier interactions rather than recent ones, and present a reranking solution. Our ELMRec outperforms state-of-the-art (SOTA) methods in both direct and sequential recommendations. Our code is available online. © 2024 Association for Computational Linguistics.

关键词： Graph embeddings

来源：评论

学校读者我要写书评

暂无评论

An Emotion-Aware Human-Computer Negotiation Model Powered by Pretrained language Model 17th

An Emotion-Aware Human-Computer Negotiation Model Powered by...

引用

17th international conference on knowledge Science, engineering and Management (KSEM)

作者： Luo, Xudong Deng, Zhiqi Sun, Kaili Lin, Pingping Guangxi Normal Univ Sch Comp Sci & Engn Guilin 541004 Guangxi Peoples R China Minist Educ Key Lab Educ Blockchain & Intelligent Technol Guilin 541004 Guangxi Peoples R China Guangxi Key Lab Multisource Informat Min & Secur Guilin 541004 Guangxi Peoples R China

ISBN: (纸本)9789819755004;9789819755011

The growth of e-commerce has led to increasing online transactions, inevitably requiring online negotiations. However, manual negotiation cannot meet the growing need. As a result, automated negotiation attracts lots of researchers. However, most work of this kind is on computer-computer negotiation and a little on human-computer one. Moreover, even the research on human-computer negotiation tends to ignore the emotional factors of human negotiators. So, it cannot deal with human emotions during a negotiation, which may significantly influence its outcome. To this end, this paper proposes a novel human-computer negotiation model. First, we fine-tune the ERNIE pretrained language model on a dataset we create. Then, the negotiating agent uses it to understand the intents and emotions of human dialogue in negotiation. Finally, the agent responds to humans according to the sentiment-related negotiation strategy we designed in this paper. Our extensive experiments show the effectiveness of our model.

关键词： Automated Negotiation Sentiment Analysis Dialogue System Pre-trained language model natural language processing

来源：评论

学校读者我要写书评

暂无评论

Hybrid Retrieval-Augmented Generation Approach for LLMs Query Response Enhancement 10

Hybrid Retrieval-Augmented Generation Approach for LLMs Quer...

引用

10th international conference on Web Research, ICWR 2024

作者： Omrani, Pouria Hosseini, Alireza Hooshanfar, Kiana Ebrahimian, Zahra Toosi, Ramin Ali Akhaee, Mohammad K. N. Toosi University of Technology Faculty of Electrical Engineering Tehran Iran Adak Vira Iranian Rahjoo Company Tehran Iran University of Tehran School of Electrical and Computer Engineering College of Engineering Tehran Iran

ISBN: (纸本)9798350394986

In the domain of natural language processing (NLP), the integration of Large language Models (LLMs) with Retrieval-Augmented Generation (RAG) represents a significant advancement towards enhancing the depth and relevance of model-generated responses. This paper introduces a novel hybrid RAG framework that synergizes the Sentence-Window and Parent-Child methodologies with an innovative re-ranking mechanism, aimed at optimizing the query response capabilities of LLMs. By leveraging external knowledge sources more effectively, the proposed method enriches LLM outputs with greater accuracy, relevance, and information fidelity. We subject our hybrid model to rigorous evaluation against benchmark datasets and metrics, demonstrating its superior performance over existing state-of-the-art RAG techniques. The results highlight our method's enhanced ability to generate responses that are not only contextually appropriate but also demonstrate a high degree of faithfulness to the source material, thereby setting a new standard for query response enhancement in LLMs. Our study underscores the potential of hybrid RAG models in refining the interaction between LLMs and external knowledge, paving the way for future research in the field of NLP. © 2024 IEEE.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Aligning Documentation and Q&A Forum through Constrained Decoding with Weak Supervision 39

Aligning Documentation and Q&A Forum through Constrained Dec...

引用

39th IEEE international conference on Software Maintenance and Evolution (ICSME)

作者： Pudari, Rohith Zhou, Shiyuan Ahmed, Iftekhar Dai, Zhuyun Zhou, Shurui Univ Toronto Toronto ON Canada Univ Calif Irvine Irvine CA 92717 USA Google Mountain View CA 94043 USA

ISBN: (纸本)9798350327830

Stack Overflow (SO) is a widely used question-andanswer (Q&A) forum dedicated to software development. It plays a supplementary role to official documentation (DOC for short) by offering practical examples and resolving uncertainties. However, the process of simultaneously consulting both the documentation and SO posts can be challenging and time-consuming due to their disconnected nature. In this study, we propose DOSA, a novel approach to automatically align SO and DOC, which inject domain-specific knowledge about the DOC structure into large language models (LLMs) through weak supervision and constrained decoding, thereby enhancing knowledge retrieval and streamlining task completion during the software development procedure. Our preliminary experiments find that DOSA outperforms various widely-used baselines, showing the promise of using generative retrieval models to perform low-resource software engineering tasks.

关键词： Stack Overflow natural language processing Constrained Decoding Weak Supervision

来源：评论

学校读者我要写书评

暂无评论

Efficient Information Retrieval: AWS Textract in Action 6th

Efficient Information Retrieval: AWS Textract in Action

引用

6th international conference on communication and computational technologies, ICCCT 2024

作者： Nancy Deborah, R. Alwyn Rajiv, S. Vinora, A. Soundarya, M. Mohammed Arif, G.S. Mohammed Arif, S. Department of IT Velammal College of Engineering and Technology Tamil Nadu Madurai India Department of ECE Kamaraj College of Engineering and Technology Tamil Nadu Madurai India

ISBN: (纸本)9789819774227

In the rapidly evolving realm of information management, the efficient and precise management of documents emerges as a fundamental necessity for businesses and organizations. AWS provides extensive text extraction services encompassing Amazon Textract, Amazon Comprehend, and Amazon Rekognition. These services harness the capabilities of machine learning and natural language processing technologies to extract valuable insights from a diverse range of document types, including invoices, contracts, forms, and images. They possess the potential to convert disorganized data into well-structured, actionable knowledge. The project initiates with an overview of AWS text extraction services, emphasizing their pivotal features. It then explores real-world uses across diverse healthcare, finance, legal, and logistics sectors. Ultimately, this project aims to spotlight the transformative potential of AWS text extraction services in reshaping document processing, elevating operational efficiency, and extracting valuable insights from previously unstructured data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

News GPT: A Large language Model for Reliable and Hallucination-Controlled News Generation 24

News GPT: A Large Language Model for Reliable and Hallucinat...

引用

3rd international Symposium on Robotics, Artificial Intelligence and Information engineering, RAIIE 2024

作者： Yao, Shunyu Ke, Qingqing Li, Kangtong Wang, Qiwei Hu, Jie Big Data and Artificial Intelligence Institute China Telecom Research Institute Beijing China China Telecom Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798400718311

With the continuous development of natural language processing (NLP) technology, large models have become essential tools for handling natural language tasks. In the news domain, large models can be used for automating news generation, thereby enhancing the productivity and quality of news production. As a result, we introduce a new large model-News GPT-which utilizes an external knowledge retrieval module to inject real information, providing authentic and reliable news generation services. By combining Chinese and English news data with general domain data, we have constructed a high-quality, multi-domain news dataset consisting of 1.4B tokens. In the pre-training phase, we expand the Chinese vocabulary for the Llama2-70B model, and in the fine-tuning phase, we design expert prompts to help the model understand downstream tasks better. We have tested News GPT in various aspects, and the experimental results show that News GPT, as an intelligent news assistant, can effectively complete tasks using retrieval tools in different application scenarios. It possesses excellent natural language understanding, knowledge, and logical reasoning abilities, and effectively controls the hallucinations in the generation process. News GPT demonstrates high accuracy and reliability in news generation and can provide substantial support for the news industry. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Autonomous agents

来源：评论

学校读者我要写书评

暂无评论

Automated Essay Grading of Constructive Response Test Responses for Mechanical engineering Students

Automated Essay Grading of Constructive Response Test Respon...

引用

IEEE international conference on Teaching, Assessment and Learning for engineering (IEEE TALE)

作者： Dung, Do Tien Mima, Hideki Triawan, Farid Cross, Jeffrey Scott Tokyo Inst Technol Sch Environm & Soc Meguro Ku Tokyo Japan Kyushu Univ Promoting Org Future Creators Nishi Ku Fukuoka Japan Sampoerna Univ Dept Mech Engn Jakarta Indonesia

ISBN: (纸本)9781665453318

Machine learning education related applications have increased with the appearance of large language models. While automatic essay grading (AEG) has been studied extensively in the past, most of these studies have focused on evaluating English competence instead of assessing knowledge competence in an engineering field. This study aimed to develop an AEG model to evaluate student's mechanical engineering Constructive Response Test (CRT) question responses which were instructor graded. Because of the small number of student responses (45), a synthesized set of responses was also generated by using text-to-text paraphrasing models. A neural network grading engine was built and trained to assess comprehension utilizing the Bidirectional Encoder Representation Transformer (BERT) and related models on student and synthesized responses. This study showed that the AEG based natural language processing (NLP) model showed high accuracy and a higher degree of consistency in grading student responses compared to instructor-graded responses.

关键词： Automatic Essay Grading Constructive Response Test Mechanical engineering

来源：评论

学校读者我要写书评

暂无评论

Exploring Text Summarization Techniques: A Review of Current Challenges and Future Directions 2

Exploring Text Summarization Techniques: A Review of Current...

引用

2nd international conference on Disruptive Technologies, ICDT 2024

作者： Kaushik, Abha Attri, Shree Harsh Jha, Ravi Shankar Computer Science and Engineering Gl Bajaj Institute of Technology and Management Greater Noida India Computer Science and Engineering Sharda University Greater Noida India School of Computing Dit University Dehradun India

ISBN: (纸本)9798350371055

Text summarization is a significant task in natural language processing (NLP) since it seeks to reduce massive amount of textual information into concise and logical summaries. The rapid expansion of digital content has raised the need for efficient text summarizing strategies. An in-depth evaluation of current trends and future directions in text summarization is provided during the investigations of summarizing techniques. This Survey begins by outlining established methodologies, such as extractive and abstractive methods, and noting their current challenges. The emergence of deep learning models in text summarization such as transformer-based models and encoderdecoder architectures will be discussed. These models have shown inspiring results in abstractive summarization and semantic meaning capture. Additionally, Investigation process carries current advances in text summarization, addressing the issues associated with summarizing information from numerous sources and languages. Along with advancement in text summarization, intriguing future avenue in text summarizing research, such as personalized summarization, domain-specific summarization, and the incorporation of external knowledge sources has also been identified. Consequences of these directions for real-world ap- plications and user preferences are analyzed. Objective is to emphasize the merits and demerits of existing approaches, identify significant difficulties, and propose potential future research directions. Finally, the goal of this review is to inspire and lead the future development of more robust and effective text summarizing algorithms. © 2024 IEEE.

关键词： deep learning models natural language processing Text Summarization transformer-based models

来源：评论

学校读者我要写书评

暂无评论

knowledge based Organizational Personal Assistant 2

Knowledge based Organizational Personal Assistant

引用

2nd international conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Mohan, Vasanthakumar Paramesh, Anandh Sivaguru Panimalar Engineering College Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9798350328202

In the modern era, most activities are being digitized. One of the main objectives of AI is to enable human machine interaction. The dialogue systems technology has been utilized by numerous organizations to create a variety of types of personal assistants depending on their applications and domains. Here we introduce the development of a versatile knowledge Based Personal Assistant for College that leverages advanced technologies, including natural language processing, voice recognition, and text to speech synthesis, to address the diverse and evolving needs of the college community. This AI driven system is designed to facilitate a seamless and efficient user experience, allowing users to interact with the assistant through both voice and text inputs. Alongside core functionalities encompassing academic schedule management, emergency contact assistance, email integration, location based services, and academic inquiries, the assistant provides responses in both voice and text formats. Technical aspects include the integration of state of the art NLP algorithms for query understanding and context aware responses. Users can easily switch between input mode and receive responses, accordingly, offering a flexible and inclusive user experience. The assistant adaptability and expandability are central to its design, featuring modular architecture that facilitates the integration of additional features and services. © 2024 IEEE.

关键词： knowledge based systems

来源：评论

学校读者我要写书评

暂无评论

Exploring Depression Through Social Media: A Textual Analysis

Exploring Depression Through Social Media: A Textual Analysi...

引用

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

作者： Bhavya, R. Ramani, Roja Royal, G.Leela Gowtham Manideep, G. Sridhar, Gautham New Horizon College of Engineering Department of Cse Bangalore India

ISBN: (纸本)9798350359688

Depression, a widespread mental health affliction, profoundly impacts individuals and societies globally. Timely intervention demands early detection, and the burgeoning realm of user-generated social media text presents a valuable avenue for understanding mental health. This thesis aims to harness machine learning techniques to establish a dependable system for identifying depression within social media text. Gathering a diverse corpus of posts from individuals with and without depression, the developed system demonstrates consistent and accurate performance across various evaluation metrics. The thesis culminates in an in-depth exploration of depression diagnosis using machine learning and natural language processing algorithms applied to social media data. Specifically, the study scrutinizes sentiment analysis and artificial intelligence methodologies for predicting emotional distress from a dataset of 20,000 English tweets obtained via the Twitter API. The analysis employs the text blob library alongside classification techniques encompassing Random Forest, KNN, Decision Tree, and Naïve Bayes model. © 2024 IEEE.

关键词： Tweets

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 << < 21 22 23 24 25 26 27 28 29 30 > >>

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：