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

1,585 篇 会议
28 册 图书
24 篇 期刊文献

馆藏范围

1,637 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,111 篇 工学
- 1,019 篇 计算机科学与技术...
- 749 篇 软件工程
- 245 篇 信息与通信工程
- 90 篇 电气工程
- 69 篇 控制科学与工程
- 67 篇 生物工程
- 42 篇 化学工程与技术
- 24 篇 仪器科学与技术
- 24 篇 安全科学与工程
- 23 篇 生物医学工程（可授...
- 21 篇 交通运输工程
- 19 篇 机械工程
- 17 篇 网络空间安全
- 16 篇 电子科学与技术（可...
- 15 篇 建筑学
361 篇 管理学
- 288 篇 图书情报与档案管...
- 108 篇 管理科学与工程(可...
- 49 篇 工商管理
343 篇 理学
- 131 篇 数学
- 124 篇 物理学
- 75 篇 生物学
- 55 篇 统计学（可授理学、...
- 48 篇 系统科学
- 41 篇 化学
41 篇 教育学
- 41 篇 教育学
38 篇 法学
- 32 篇 社会学
37 篇 文学
- 31 篇 外国语言文学
30 篇 医学
- 27 篇 临床医学
- 22 篇 基础医学(可授医学...
19 篇 农学
- 17 篇 作物学
14 篇 经济学
4 篇 军事学

主题

184 篇 natural language...
64 篇 natural language...
55 篇 semantics
50 篇 web services
46 篇 sentiment analys...
42 篇 computational mo...
42 篇 accuracy
41 篇 deep learning
40 篇 information retr...
37 篇 data mining
36 篇 machine learning
36 篇 classification (...
35 篇 artificial intel...
33 篇 ontology
31 篇 speech recogniti...
31 篇 training
29 篇 data models
28 篇 semantic web
26 篇 search engines
26 篇 feature extracti...

机构

7 篇 spoken language ...
7 篇 sri lanka instit...
7 篇 faculty of compu...
6 篇 faculty of infor...
4 篇 key laboratory o...
4 篇 fujian yirong in...
4 篇 korea univ nat l...
4 篇 school of inform...
4 篇 international in...
4 篇 information engi...
3 篇 big data and art...
3 篇 graduate school ...
3 篇 national univers...
3 篇 institute of art...
3 篇 carnegie mellon ...
3 篇 school of inform...
3 篇 chitkara univers...
3 篇 beijing univ pos...
3 篇 ipswich
3 篇 department of in...

作者

7 篇 nakagawa seiichi
5 篇 ren fuji
5 篇 zhao tiejun
5 篇 rim hae-chang
4 篇 heyan huang
4 篇 shikano kiyohiro
4 篇 fuji ren
4 篇 liu ting
3 篇 li li
3 篇 rykowski jarogni...
3 篇 nakamura satoshi
3 篇 zheng dequan
3 篇 ngoc thanh nguye...
3 篇 medhat walaa
3 篇 kinshuk
3 篇 bogdan trawiński
3 篇 sun xu
3 篇 mizera-pietraszk...
3 篇 bollegala danush...
3 篇 kitsuregawa masa...

语言

1,597 篇 英文
37 篇 其他
10 篇 中文

检索条件"任意字段=6th International Conference on Advanced Language Processing and Web Information Technology"

共 1637 条记录，以下是431-440 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：

Machine Translation into Low-resource language Varieties 59

Machine Translation into Low-resource Language Varieties

引用

Joint conference of 59th Annual Meeting of the Association-for-Computational-Linguistics (ACL) / 11th international Joint conference on Natural language processing (IJCNLP) / 6th Workshop on Representation Learning for NLP (RepL4NLP)

作者： Kumar, Sachin Anastasopoulos, Antonios Wintner, Shuly Tsvetkov, Yulia Carnegie Mellon Univ Language Technol Inst Pittsburgh PA 15213 USA George Mason Univ Dept Comp Sci Fairfax VA 22030 USA Univ Haifa Dept Comp Sci Haifa Israel Univ Washington Paul G Allen Sch Comp Sci & Engn Seattle WA 98195 USA

ISBN: (纸本)9781954085534

State-of-the-art machine translation (MT) systems are typically trained to generate "standard" target language;however, many languages have multiple varieties (regional varieties, dialects, sociolects, non-native varieties) that are different from the standard language. Such varieties are often low-resource, and hence do not benefit from contemporary NLP solutions, MT included. We propose a general framework to rapidly adapt MT systems to generate language varieties that are close to, but different from, the standard target language, using no parallel (source-variety) data. this also includes adaptation of MT systems to low-resource typologically-related target languages.1 We experiment with adapting an English-Russian MT system to generate Ukrainian and Belarusian, an English-Norwegian Bokmal system to generate Nynorsk, and an English-Arabic system to generate four Arabic dialects, obtaining significant improvements over competitive baselines.

关键词： Machine translation

来源：评论

学校读者我要写书评

暂无评论

Large-language-Models (LLM)-Based AI Chatbots: Architecture, In-Depth Analysis and their Performance Evaluation 6th

Large-Language-Models (LLM)-Based AI Chatbots: Architecture,...

引用

6th international conference on Recent Trends in Image processing and Pattern Recognition, RTIP2R 2023

作者： Kumar, Vimal Srivastava, Priyam Dwivedi, Ashay Budhiraja, Ishan Ghosh, Debjani Goyal, Vikas Arora, Ruchika Bennett University Uttar Pradesh Greater Noida India Directorate of Secondary Education Haryana Panchkula India SR University Ananthasagar Telangana Warangal India

ISBN: (纸本)9783031530845

this scholarly article conducts a comparative evaluation of prominent large-scale language models, specifically encompassing Google’s BARD, ChatGPT 3.5, and ChatGPT 4. It offers a comprehensive dissection of each model, elucidating aspects such as architectural structure, utilized training data, and proficiency in natural language processing. the paper also undertakes a systematic assessment of these models in executing diverse tasks like text generation, text completion, and question-answering, paralleling their precision, processing speed, and efficiency. the concluding part of the article explores the prospective application domains of these language models, including but not limited to customer service, education, and healthcare sectors, while proffering suggestions for future research trajectories and technological enhancements. In summary, the study furnishes critical insights into the current status of large-scale language models, shedding light on their potential to augment human-computer interaction and drive forward advancements in the realm of natural language processing technology. © 2024, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Personal Identity information Detection using Synthetic Dataset

Personal Identity Information Detection using Synthetic Data...

引用

Applied Computational Intelligence in information Systems (ACIIS), international conference on

作者： Tan Jie Lin Nalam Venkata Abhishek Information and Communication Technology Cluster Singapore Institute of Technology

Safeguarding Personal Identity information (PII) is essential to protect privacy, prevent identity theft, comply with laws, maintain trust, and ensure national security. Unauthorized access or disclosure of PII can have severe consequences, including financial fraud and reputation damage. With the increasing attention paid to safeguarding personal details online, the identification of PII has become crucial for protecting sensitive and private information. this paper addresses the effectiveness of PII detection using different Natural language processing (NLP) techniques trained with synthetic PII data. three different methods were experimented with for generating appropriate synthetic data. Furthermore, the data is pre-processed to ensure that the final generated dataset is meaningful and usable. this generated dataset will be used to train state-of-the-art NLP models, namely spaCy, BERT, and biLSTM. It is important to note that the synthetic data generated will be processed based on each model’s required format and then trained or fine-tuned. Performance evaluation is conducted for each model, where the best-performing model will be used to create a sustainable PII detection tool. the metrics precision, recall, and F1 score are used to compare the performance of the above NLP models.

关键词：

来源：评论

学校读者我要写书评

暂无评论

the Design and Implementation of an Intelligent Q&A System for Electric Power Safety Regulations Based on Large language Model technology

The Design and Implementation of an Intelligent Q&A System f...

引用

Energy Systems and Electrical Power (ICESEP), international conference on

作者： Bochu Li Yan Jiang Jie Xu Zheng Liu Zhiqiang Sheng Xueying Song Fuqiang Chen Zibing Meng Beijing Fibrlink Communications Co. Ltd Beijing China State Grid Information & TeleCommunication Group Co. Ltd Beijing China State Grid Wuxi Power Supply Company Wuxi Jiangsu China

ISBN: (数字)9798350353563

ISBN: (纸本)9798350353570

In response to the challenges of the vast and scattered content, as well as the low efficiency in learning and searching within the safety regulations in the field of electric power, an intelligent question-answering system has been designed based on large model technology. this system aims to organize knowledge related to safety regulations and improve search efficiency. the system employs natural language processing techniques to categorize entries in safety regulations. It utilizes a vector database for entry vectorization and storage. the integration of large models with safety regulation entries is achieved through a large model development framework, forming a question-answering system. A file management module is constructed using a frontend framework to provide interactive functionality to the question-answering system. the performance experiment of the system on the question answering system shows that the overall accuracy of the system's answer to the safety rules and regulations in the field of electric power is more than 60%, which is professional than the general large model.

关键词： Accuracy Large language models Text summarization Regulation Vectors Question answering (information retrieval) Power industry

来源：评论

学校读者我要写书评

暂无评论

Enhancing the Automatic Identification of Common Math Misconceptions Using Natural language processing 24th

Enhancing the Automatic Identification of Common Math Miscon...

引用

24th international conference on Artificial Intelligence in Education (AIED)

作者： Gorgun, Guher Botelho, Anthony F. Univ Alberta Edmonton AB T6G 2G5 Canada Univ Florida Gainesville FL 32611 USA

ISBN: (纸本)9783031363351;9783031363368

In order to facilitate student learning, it is important to identify and remediate misconceptions and incomplete knowledge pertaining to the assigned material. In the domain of mathematics, prior research with computer-based learning systems has utilized the commonality of incorrect answers to problems as a way of identifying potential misconceptions among students. Much of this research, however, has been limited to the use of close-ended questions, such as multiple-choice and fill-in-the-blank problems. In this study, we explore the potential usage of natural language processing and clustering methods to examine potential misconceptions across student answers to both close- and open-ended problems. We find that our proposed methods show promise for distinguishing misconception from non-conception, but may need further development to improve the interpretability of specific misunderstandings exhibited through student explanations.

关键词： misconceptions sentence-BERT intelligent tutoring system natural language processing

来源：评论

学校读者我要写书评

暂无评论

Vision AI: Enhancing Ophthalmic Care with advanced Detection Technologies

Vision AI: Enhancing Ophthalmic Care with Advanced Detection...

引用

Advancements in Computing (ICAC), international conference on

作者： S. M. K. S. Siriwardana S. N. W. Gunasekara W. U. Piyumantha S. P. thilakaratne D. R. Wijendra D. I. de Silva Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

this study presents Vision AI, an advanced diagnostic framework that utilizes hybrid deep learning models for accurate detection of eye diseases, specifically Glaucoma, Macular Hole, Central Serous Retinopathy, and Drusen. Traditional ophthalmic diagnostics often suffer from human error and inefficiencies, emphasizing the need for automated solutions. Vision AI addresses these challenges by integrating multiple model architectures, such as VGG16, ResNet, V-Net, and YOLOv8x, optimizing diagnostic accuracy and generalizability. A carefully curated dataset of retinal images was used, supported by extensive data augmentation and hyperparameter tuning to enhance model robustness. this approach significantly improved detection capabilities, achieving over 95% specificity and sensitivity across diseases. Additionally, Vision AI includes a Large language Model for providing tailored health recommendations, making the system highly practical for clinical use. the framework is deployed in a scalable microservice-based web application, ensuring modularity, security, and real-time diagnostics, thus improving accessibility for healthcare providers. Vision AI showcases the potential of hybrid deep learning systems to transform ophthalmic care, laying a foundation for AI-assisted, patient-centered healthcare advancements.

关键词： Deep learning Glaucoma Technological innovation Accuracy Sensitivity Transforms Retina Robustness Security Tuning

来源：评论

学校读者我要写书评

暂无评论

Extraction Method of Judicial language Entities Based on Regular Expression 6

Extraction Method of Judicial Language Entities Based on Reg...

引用

6th IEEE international conference on Intelligent Computing and Signal processing, ICSP 2021

作者： Kainan, Jiao Xin, L.I. People's Public Security University of China School of Information Network Security Beijing China

ISBN: (纸本)9780738143705

With the coming of the era of rule of law and intelligence, natural language processing technology plays a pivotal role. At present, a large number of unstructured judicial texts rely on manual processing and archiving. In order to make better use of them and achieve professional application, this paper proposes the goal of analyzing the structure of judgments, extracting the judicial language entities, and describing cases in the form of entity circulation map. As the text carrier of unstructured public events, the judicial document is of better standard format, finely crafted and easy processing, and becomes the research object of this paper. through the survey of the development of named entity recognition technology, testing and contrasting the use of extraction tool, GATE, as well as considering the cost and effectiveness in the judicial field, this paper put forward a rule-based regular expression method for entity recognition. the scrapy crawler framework is used to obtain judgments classified from China Judgments Online website, so as to realize the task of analyzing the structure of judgments and extracting the judicial language entities. © 2021 IEEE.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

User Interest Prediction based on Social Network Profile with Machine Learning 6

User Interest Prediction based on Social Network Profile wit...

引用

6th international conference for Convergence in technology (I2CT)

作者： Krishna, Hari S. M. Hegde, Shridhar Santosh, G. Shivakumar, M. Srihari, R. Lakshmi, Shree N. MS Ramaiah Univ Appl Sci Dept Comp Sci & Engn Bangalore Karnataka India

ISBN: (纸本)9781728188768

the explosion of social media data which holds important, massive, rapidly evolving unstructured information has provided an opportunity to research public opinion and know people's feelings. Capturing the views on social events, corporate strategies, political movements, marketing campaigns and product preferences et cetera brings growing interest from the scientific and business communities to improve their performances. this has resulted in an emerging field of social network mining or sentiment analysis. this paper describes a system that was built to analyze data from social media platforms such as Twitter, Instagram, Facebook and Reddit. the data is gathered from various services and programs which involves using the official API's and scraping tools. Machine Learning & Image processing algorithms are applied on the gathered data to gain insights about the individual users' interests, usage patterns, media reachability, et cetera. these models are then relayed to a web application where various visualizations of the insights can be obtained.

关键词： Data Analysis Social Network Mining Machine Learning Image processing Data Visualization

来源：评论

学校读者我要写书评

暂无评论

Robotic Process Automation for Resume processing System 6

Robotic Process Automation for Resume Processing System

引用

6th international conference on Recent Trends on Electronics, information, Communication and technology, RTEICT 2021

作者： Roopesh, N. Babu, C. Narendra M S Ramaiah University of Applied Sciences Dept. of CSE India

ISBN: (纸本)9781665435598

Recruiting a right candidate for a particular job is a tedious process as shortlisting few applications among thousands involves huge man power. Once the candidates are short listed then candidates have to go through different levels of interviews. Now a day's companies relay on third party for conducting the initial round of interviews. this paper aims to automate such interview process to help in recruitment with the help of robotic process automation and machine learning techniques. RPA bot monitors the mail and the file storage, if any new mail or file are received, the attachment with respect to the mails are downloaded and document classification is done on the attachments to find if they are resumes, text is extracted from the attachments, Name Entity Recognition (NER) is applied to get the important details in the attachments and the resumes are short listed based on the skills, experience and the education background. the precision value for text classification done with Naive Bayes Classifier is 92.08%, for document classification with 150k Bag of Words on BERT is 91.36%, for custom trained NER is 86.2% and finally for web scranning is 91.56%. © 2021 IEEE.

关键词： Robotics

来源：评论

学校读者我要写书评

暂无评论

Constructing a Medical Domain Functional Knowledge Graph with Large language Models

Constructing a Medical Domain Functional Knowledge Graph wit...

引用

IEEE international conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Lintian Ji Shuxin Du Yi Qiu Hongyi Xu Xiaorui Guo Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems School of Engineering Huzhou University Huzhou China Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems School of Engineering Huzhou University Huzhou China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

the integration of medicine and artificial intelligence is creating novel opportunities to gather, analyze, and generate groundbreaking medical insights from the vast expanse of medical literature. Although these advancements hold great promise, difficulties including manual annotation and precise data retrieval, and transparency persist. advanced natural language processing (NLP) techniques and large language models (LLMs) have shown potential in addressing these issues. this paper introduces the Medical Knowledge Graph (MedKG), a comprehensive and multidisciplinary medical knowledge graph. By utilizing advanced NLP algorithms, MedKG extracts millions of entities and converts them into triples from a corpus of superior medical research papers published over the last decade. It categorizes unstructured medical information into nine distinct tags, including disease names, treatments, diagnoses, symptoms, genetics, cellular structures of diseases, patient data, medical procedures, and treatment applications, while seamlessly integrating the digital object identifier (DOI) of each paper. As the latest structured database of medical knowledge, MedKG serves as a powerful tool for accelerating medical research and lays the groundwork for constructing a more extensive medical knowledge graph using full-text medical articles. Moreover, our research establishes a foundation for practical knowledge management systems based on text mining, applicable not only to complex medical systems but also to other professional domains.

关键词： Text mining Annotations Large language models Pipelines Knowledge graphs Prediction algorithms Natural language processing Object recognition Medical diagnostic imaging Diseases

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164页 << < 40 41 42 43 44 45 46 47 48 49 > >>

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：