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

14,549 篇 会议
662 篇 期刊文献
101 册 图书
40 篇 学位论文
1 篇 科技报告

馆藏范围

15,352 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

11,015 篇 工学
- 10,349 篇 计算机科学与技术...
- 5,460 篇 软件工程
- 1,467 篇 信息与通信工程
- 956 篇 电气工程
- 892 篇 控制科学与工程
- 447 篇 生物工程
- 221 篇 网络空间安全
- 220 篇 化学工程与技术
- 186 篇 机械工程
- 177 篇 生物医学工程（可授...
- 141 篇 电子科学与技术（可...
- 101 篇 仪器科学与技术
- 100 篇 安全科学与工程
2,486 篇 理学
- 1,156 篇 数学
- 654 篇 物理学
- 520 篇 生物学
- 394 篇 统计学（可授理学、...
- 241 篇 系统科学
- 232 篇 化学
2,427 篇 管理学
- 1,756 篇 图书情报与档案管...
- 759 篇 管理科学与工程(可...
- 241 篇 工商管理
- 106 篇 公共管理
1,762 篇 文学
- 1,710 篇 外国语言文学
- 184 篇 中国语言文学
515 篇 医学
- 303 篇 临床医学
- 286 篇 基础医学(可授医学...
- 113 篇 公共卫生与预防医...
279 篇 法学
- 249 篇 社会学
239 篇 教育学
- 226 篇 教育学
100 篇 农学
96 篇 经济学
10 篇 艺术学
7 篇 哲学
4 篇 军事学

主题

3,552 篇 natural language...
1,789 篇 natural language...
953 篇 computational li...
741 篇 semantics
683 篇 machine learning
612 篇 deep learning
520 篇 natural language...
352 篇 computational mo...
343 篇 accuracy
339 篇 training
334 篇 large language m...
334 篇 sentiment analys...
325 篇 feature extracti...
312 篇 data mining
290 篇 speech processin...
260 篇 speech recogniti...
255 篇 transformers
236 篇 neural networks
218 篇 iterative method...
212 篇 support vector m...

机构

85 篇 carnegie mellon ...
51 篇 university of ch...
46 篇 tsinghua univers...
45 篇 carnegie mellon ...
43 篇 zhejiang univers...
43 篇 national univers...
38 篇 nanyang technolo...
36 篇 university of sc...
36 篇 university of wa...
35 篇 univ chinese aca...
34 篇 carnegie mellon ...
33 篇 stanford univers...
32 篇 gaoling school o...
32 篇 alibaba grp peop...
31 篇 school of artifi...
29 篇 tsinghua univ de...
28 篇 harbin institute...
27 篇 peking universit...
26 篇 microsoft resear...
26 篇 language technol...

作者

55 篇 zhou guodong
50 篇 neubig graham
46 篇 liu yang
39 篇 sun maosong
36 篇 zhang min
34 篇 liu qun
33 篇 smith noah a.
28 篇 schütze hinrich
26 篇 wen ji-rong
26 篇 liu zhiyuan
26 篇 lapata mirella
24 篇 chang kai-wei
23 篇 zhou jie
23 篇 yang diyi
23 篇 zhao hai
23 篇 zhao wayne xin
21 篇 chua tat-seng
20 篇 dredze mark
18 篇 biemann chris
18 篇 fung pascale

语言

14,307 篇 英文
930 篇 其他
114 篇 中文
18 篇 法文
14 篇 土耳其文
2 篇 德文
2 篇 西班牙文
2 篇 俄文

检索条件"任意字段=Conference on empirical methods in natural language processing"

共 15353 条记录，以下是4571-4580 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：

An empirical Evaluation of Out-of-Distribution Detection Using Pretrained language Models

An Empirical Evaluation of Out-of-Distribution Detection Usi...

引用

International conference on Control and Robots (ICCR)

作者： Byungmu Yoon Jaeyoung Kim Gachon University Seongnam-si Gyeonggi-do Korea

In natural language processing (NLP) tasks, detecting out-of-distribution (OOD) samples is essential to safely deploy a language model in real-world problems. Recently, several studies report that pre-trained language models (PLMs) accurately detect OOD data compared to LSTM, but we empirically find that PLMs show sub-par OOD detection performance when (1) OOD samples have similar semantic representation to in-distribution (IND) samples and (2) PLMs are finetuned under data scarcity settings. To alleviate above issues, state-of-the-art uncertainty quantification (UQ) methods can be used, but the comprehensive analysis of UQ methods with PLMs has received little consideration. In this work, we investigate seven UQ methods with PLMs and show their effectiveness in the text classification task.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Leveraging Text Representation and Face-head Tracking for Long-form Multimodal Semantic Relation Understanding 22

Leveraging Text Representation and Face-head Tracking for Lo...

引用

30th ACM International conference on Multimedia (MM)

作者： Ramesh, Raksha Anand, Vishal Chen, Zifan Dong, Yifei Chen, Yun Lin, Ching-Yung Columbia Univ New York NY 10027 USA Graphen Inc New York NY USA Microsoft Corp Redmond WA 98052 USA

ISBN: (纸本)9781450392037

In the intricate problem of understanding long-form multi-modal inputs, few key-aspects in scene-understanding and dialogue-and-discourse are often overlooked. In this paper, we investigate two such key-aspects for better semantic and relational understanding (i). head-object-tracking in addition to usual face-tracking, and (ii). fusing scene-to-text representation with external common-sense knowledge-base for effective mapping to sub-tasks of interest. The usage of head-tracking especially helps with enriching sparse entity mapping to inter-entity conversation interactions. These methods are guided by natural language supervision on visual models, and perform well for interaction and sentiment understanding tasks.

关键词： natural language processing object tracking dialogue and discourse language models slot filling intent detection knowledge graphs speaker diarization

来源：评论

学校读者我要写书评

暂无评论

Design and Optimization of an Intelligent English Interaction System Based on Speech Recognition and natural language processing Technology

Design and Optimization of an Intelligent English Interactio...

引用

Education, Network and Information Technology (ICENIT), International conference on

作者： Bingbing Wang Jilin Animation Institute Changchun China

ISBN: (数字)9798350374919

ISBN: (纸本)9798350374926

With the rapid development of globalization, traditional learning methods have significant limitations in speaking practice and struggle to meet the personalized needs of learners. Innovative educational tools are needed to enhance students' speaking skills. This paper proposes a design and optimization plan for an intelligent English interactive system based on speech recognition and natural language processing technologies. It explores the adaptability of speech recognition technology under different accents, speech rates, and noise environments. By optimizing deep learning models, the accuracy of recognition is further improved. Meanwhile, by integrating natural language processing technology, the system understands user intentions and generates natural responses, enhancing the fluency of human-computer dialogue. In the system design, a modular architecture is adopted to facilitate later optimization, implementing core functional modules for speech recognition, natural language understanding, dialogue management, natural language generation, and speech synthesis. Experimental validation shows that the optimized system significantly improves recognition accuracy in multiple scenarios, performing particularly well in processing movie dialogues and everyday conversations. The research results indicate that the system designed in this paper not only enhances the English learning experience but also provides an effective technical path for the development of intelligent interactive systems.

关键词： Accuracy Interactive systems Noise Speech recognition Oral communication Motion pictures natural language processing Stability analysis Optimization System analysis and design

来源：评论

学校读者我要写书评

暂无评论

Social Media Sentiment and Stock Return: A Signaling Theory Explanation for Application of the natural Langrage processing Approaches 33

Social Media Sentiment and Stock Return: A Signaling Theory ...

引用

33rd Australasian conference on Information Systems: The Changing Face of IS, ACIS 2022

作者： Qin, Chuan Miah, Shah J. Shao, David Xuefeng Newcastle Business School The University of Newcastle CallaghanNSW Australia

Social media, especially microblogs, have potentials to develop unavoidable factors in investment decision-making, because of its use for capturing human sentiment. In this paper, by applying signaling theory and natural language processing (NLP) technique, we concern social media sentiment as a signal to stock return which is based on human the sentiment, which may lead to price fluctuation in the market. We take the strength of signal into consideration, introducing the sentiment of traditional media to compare with social media sentiment in different industry. The empirical result of this paper will prove the relationship between social media sentiment and stock return. It will also reflect on analyzing the changes of stock price given different strength of signals in both positive and negative way. The entire study will be viewed as a guideline for investors to filter and smartly use the huge numbers of information when making investment decision. Copyright © 2022 Qin, Miah, and Shao.

关键词： Investments

来源：评论

学校读者我要写书评

暂无评论

Text Regression Analysis for Predictive Intervals Using Gradient Boosting 1

引用

8th Future of Information and Communication conference (FICC)

作者： Iliev, Alexander I. Raksha, Ankitha SRH Berlin Univ Berlin Germany Bulgarian Acad Sci Inst Math & Informat Sofia Bulgaria

ISBN: (数字)9783031280733

ISBN: (纸本)9783031280726;9783031280733

In this paper, we aim to explore text data analysis with the help of different methods to vectorize the data and carry out regression methods. At present, we have a lot of text categorization techniques, but very few algorithms are dedicated to text regression. But many regression models predict only a single estimated value. However, it's more efficient to predict a numerical range than a single estimate, since we can be more sure that the true value will be within the range rather than considering the estimated value as the true value. We aim to combine both these techniques in this paper. The goal of this paper is to collect text data, clean the data, and create a text regression model to find the best-suited algorithm that could be used in any situation, through the use of quantile regression.

关键词： Text analysis tf-.idf word2vec GloVe Text regression Word vectorization Quantile Gradient boosting natural language processing

来源：评论

学校读者我要写书评

暂无评论

IoT Software Vulnerability Detection Techniques through Large language Model 24th

IoT Software Vulnerability Detection Techniques through Larg...

引用

24th International conference on Formal Engineering methods, ICFEM 2023

作者： Yang, Yilin School of Computer Science and Engineering UNSW Sydney Sydney Australia

ISBN: (纸本)9789819975839

The explosion of IoT usage provides efficiency and convenience in various fields including daily life, business and information technology. However, there are potential risks in large-scale IoT systems and vulnerability detection plays a significant role in the application of IoT. Besides, traditional approaches like routine security audits are expensive. Thus, substitution methods with lower costs are needed to achieve IoT system vulnerability detection. LLMs, as new tools, show exceptional natural language processing capabilities, meanwhile, static code analysis offers low-cost software analysis avenues. The paper aims at the combination of LLMs and static code analysis, implemented by prompt engineering, which not only expands the application of LLMs but also provides a probability of accomplishing cost-effective IoT vulnerability software detection. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cost effectiveness

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Similarity methods in High-Dimensional Vectors: A Review

Comparative Analysis of Similarity Methods in High-Dimension...

引用

2023 International conference on Artificial Intelligence Science and Applications in Industry and Society, CAISAIS 2023

作者： Yasser, Mohammad Hussain, Khaled F. Ali, Samia A. Assiut University Department of Electrical Engineering Assiut city Assiut Egypt Assiut University Faculty of Computers and Information Assiut city Assiut Egypt

ISBN: (纸本)9798350314786

With the increasing availability of high-dimensional data in diverse fields as well as the need to process this data, the accurate measurement of similarity plays a crucial role in many applications. Specifically, the machine learning models that check for similarity between given items need methods that are both time efficient and accurate. The exploration of high-dimensional data has become increasingly crucial in diverse fields, including natural language processing, computer vision, bioinformatics, and more. This paper presents a comprehensive comparison of various similarity methods in high-dimensional vectors. This paper is concerned with evaluating and analyzing a number of different similarity methods, considering their effectiveness, efficiency, and robustness in capturing similarities within high-dimensional datasets. The methods shown were tested on a total of 11 open source benchmark data sets The experimental results on various datasets demonstrate the strengths and limitations of each method, providing valuable insights for researchers and practitioners in selecting appropriate similarity measures for their specific needs. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Automatic Extraction and Formalization of Temporal Requirements from Text: A Survey 28th

Automatic Extraction and Formalization of Temporal Require...

引用

28th International conference on Enterprise Design, Operations, and Computing, EDOC 2024

作者： Barrientos, Marisol Winter, Karolin Rinderle-Ma, Stefanie Technical University of Munich Garching Germany Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9783031783371

natural language processing has opened new paths for business process management and requirements engineering, particularly in automating the extraction and formalization of temporal requirements from diverse documents such as system specifications, legal texts, and business process descriptions. Recently, approaches have been introduced to automate this task, employing various document formats as input and targeting different formal specifications. However, a key challenge persists: effectively comparing these approaches and choosing the most suitable one for a specific task. This paper aims to bridge this research gap by conducting a systematic literature review, including a detailed analysis and comparing existing approaches. This comparison is crucial to determine if the latest Large language Model-based solutions could surpass existing methods in effectiveness and ease of use. The systematic literature review enables users to select the most suitable method based on their data and end goals. Moreover, this work proposes the NL2MTL (https://***/marisol-barrientos/nl2mtl, DLA: 22.04.2024) method to bridge some of the gaps identified in the literature analysis, i.e., establishing a comparable assessment method, under-representation of legal texts, poor output context management, and the necessity to automate the formalization of requirements, considering both quantitative and qualitative aspects of time. Addressing the latter aspect, we select Metric Temporal Logic (MTL) as formalization and provide the associated prompts and an evaluation of the NL2MTL output. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Administrative data processing

来源：评论

学校读者我要写书评

暂无评论

SA²VP: Spatially Aligned-and-Adapted Visual Prompt 38

SA<SUP>2</SUP>VP: Spatially Aligned-and-Adapted Visual Promp...

引用

38th AAAI conference on Artificial Intelligence (AAAI) / 36th conference on Innovative Applications of Artificial Intelligence / 14th Symposium on Educational Advances in Artificial Intelligence

作者： Pei, Wenjie Xia, Tongqi Chen, Fanglin Li, Jinsong Tian, Jiandong Lu, Guangming Harbin Inst Technol Shenzhen Peoples R China Shenzhen Jiang Associates Creat Design Co Ltd Shenzhen Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang Peoples R China

ISBN: (纸本)1577358872

As a prominent parameter-efficient fine-tuning technique in NLP, prompt tuning is being explored its potential in computer vision. Typical methods for visual prompt tuning follow the sequential modeling paradigm stemming from NLP, which represents an input image as a flattened sequence of token embeddings and then learns a set of unordered parameterized tokens prefixed to the sequence representation as the visual prompts for task adaptation of large vision models. While such sequential modeling paradigm of visual prompt has shown great promise, there are two potential limitations. First, the learned visual prompts cannot model the underlying spatial relations in the input image, which is crucial for image encoding. Second, since all prompt tokens play the same role of prompting for all image tokens without distinction, it lacks the fine-grained prompting capability, i. e., individual prompting for different image tokens. In this work, we propose the Spatially Aligned-and-Adapted Visual Prompt model (SA2VP), which learns a two-dimensional prompt token map with equal (or scaled) size to the image token map, thereby being able to spatially align with the image map. Each prompt token is designated to prompt knowledge only for the spatially corresponding image tokens. As a result, our model can conduct individual prompting for different image tokens in a fine-grained manner. Moreover, benefiting from the capability of preserving the spatial structure by the learned prompt token map, our SA2VP is able to model the spatial relations in the input image, leading to more effective prompting. Extensive experiments on three challenging benchmarks for image classification demonstrate the superiority of our model over other state-of-the-art methods for visual prompt tuning. Code is available at https://***/tommy-xq/SA2VP.

关键词： natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

NLP based Text Summarization of Fintech RFPs 2

NLP based Text Summarization of Fintech RFPs

引用

2nd International conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023

作者： Patil, Krutika Badamikar, Medha Sonawane, Sheetal Pune Institute of Computer Technology Department of Computer Engineering Pune India

ISBN: (纸本)9781665491990

In today's day and age, where huge quantities of textual data are generated every second, it has become difficult to keep ourselves abreast with new information. Documents in the financial sector tell a quantitative story. The qualitative or language content that accompanies financial statements is an essential component of the information set used by financial market participants for monitoring and stewardship. This necessitates the development of efficient technological methods for leveraging the existence of these massive amounts of textual data. Reading financial documents such as annual reports is extremely time-consuming and thus corporations have to allocate precious human capital to understand, analyze and derive insight from these reports. As a result, automatic summarization techniques can make this task simpler by enabling access to a smaller but informative portion of a given document. In this work, a system utilizing NLP techniques for summarizing financial documents based on queries provided by the user, is presented. This system overcomes the challenges posed by existing section-based summarization models. As machine learning methods have proven to be effective on downstream tasks such as text summarization, the intent of this work is to take advantage of these methods for effective extractive summarization and generate human-like summaries. The proposed model categorizes phrases according to their relevance by leveraging the strength of unsupervised clustering approaches, and it gets a ROUGE-1 score of 46%. © 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

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 << < 454 455 456 457 458 459 460 461 462 463 > >>

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：