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

577 篇 会议
3 册 图书

馆藏范围

580 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

362 篇 工学
- 355 篇 计算机科学与技术...
- 225 篇 软件工程
- 60 篇 信息与通信工程
- 41 篇 生物工程
- 34 篇 控制科学与工程
- 26 篇 电气工程
- 18 篇 生物医学工程（可授...
- 17 篇 网络空间安全
- 14 篇 石油与天然气工程
- 11 篇 化学工程与技术
- 10 篇 光学工程
- 5 篇 安全科学与工程
- 4 篇 仪器科学与技术
- 4 篇 建筑学
112 篇 理学
- 56 篇 数学
- 42 篇 生物学
- 23 篇 统计学（可授理学、...
- 22 篇 物理学
- 20 篇 系统科学
- 10 篇 化学
94 篇 管理学
- 59 篇 图书情报与档案管...
- 39 篇 管理科学与工程(可...
- 17 篇 工商管理
23 篇 文学
- 21 篇 外国语言文学
14 篇 医学
- 11 篇 临床医学
- 10 篇 基础医学(可授医学...
- 6 篇 药学(可授医学、理...
13 篇 教育学
- 13 篇 教育学
11 篇 法学
- 10 篇 社会学
8 篇 经济学
- 8 篇 应用经济学
3 篇 农学
1 篇 军事学

主题

131 篇 natural language...
129 篇 machine learning
64 篇 deep learning
44 篇 accuracy
40 篇 training
35 篇 sentiment analys...
30 篇 feature extracti...
27 篇 adversarial mach...
25 篇 data models
24 篇 semantics
23 篇 machine learning...
22 篇 computational mo...
20 篇 analytical model...
18 篇 data mining
18 篇 natural language...
18 篇 adaptation model...
17 篇 contrastive lear...
17 篇 predictive model...
16 篇 support vector m...
15 篇 transformers

机构

4 篇 shanghai jiao to...
3 篇 carnegie mellon ...
3 篇 pune
3 篇 school of mathem...
3 篇 shanghai maritim...
3 篇 school of comput...
3 篇 manipal universi...
2 篇 wuhan institute ...
2 篇 wuhan second shi...
2 篇 department of ar...
2 篇 changchun univer...
2 篇 sctr's pune inst...
2 篇 school of comput...
2 篇 commercial aircr...
2 篇 shandong univers...
2 篇 jilin animation ...
2 篇 the hong kong po...
2 篇 jinan university
2 篇 silc business sc...
2 篇 guangdong instit...

作者

3 篇 shengyang li
3 篇 hong huo
3 篇 shijie yang
3 篇 tao fang
3 篇 yunfei liu
2 篇 mouncif hicham
2 篇 ukhalkar prakash
2 篇 sharma neha
2 篇 rudi sutomo
2 篇 andersson karl
2 篇 herwig unger
2 篇 lingyun zhao
2 篇 bing gu
2 篇 fang tao
2 篇 longfei li
2 篇 li yuancheng
2 篇 bhate manasi
2 篇 tasnim farzana
2 篇 li hong
2 篇 bagade anant m.

语言

549 篇 英文
30 篇 其他
2 篇 中文

检索条件"任意字段=7th International Conference on Machine Learning and Natural Language Processing, MLNLP 2024"

共 580 条记录，以下是51-60 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：

A Unified learning Framework of Skip-Grams and Global Vectors 53

A Unified Learning Framework of Skip-Grams and Global Vector...

引用

53rd Annual Meeting of the Association-for-Computational-Linguistics (ACS) / 7th international Joint conference on natural language processing of the Asian-Federation-of-natural-language-processing (IJCNLP)

作者： Suzuki, Jun Nagata, Masaaki NTT Corp NTT Commun Sci Labs 2-4 HikaridaiSeika Cho Kyoto 6190237 Japan

ISBN: (纸本)9781941643730

Log-bilinear language models such as SkipGram and GloVe have been proven to capture high quality syntactic and semantic relationships between words in a vector space. We revisit the relationship between SkipGram and GloVe models from a machine learning viewpoint, and show that these two methods are easily merged into a unified form. then, by using the unified form, we extract the factors of the configurations that they use differently. We also empirically investigate which factor is responsible for the performance difference often observed in widely examined word similarity and analogy tasks.

关键词： Vector spaces

来源：评论

学校读者我要写书评

暂无评论

Recovering dropped pronouns from Chinese text messages 53

Recovering dropped pronouns from Chinese text messages

引用

作者： Yang, Yaqin Liu, Yalin Xu, Nianwen Paypal Inc San Jose CA 95131 USA Brandeis Univ Waltham MA 02254 USA

ISBN: (纸本)9781941643730

Pronouns are frequently dropped in Chinese sentences, especially in informal data such as text messages. In this work we propose a solution to recover dropped pronouns in SMS data. We manually annotate dropped pronouns in 684 SMS files and apply machine learning algorithms to recover them, leveraging lexical, contextual and syntactic information as features. We believe this is the first work on recovering dropped pronouns in Chinese text messages.

关键词： learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Non-linear learning for Statistical machine Translation 53

Non-linear Learning for Statistical Machine Translation

引用

作者： Huang, Shujian Chen, Huadong Dai, Xinyu Chen, Jiajun Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Jiangsu Peoples R China

ISBN: (纸本)9781941643723

Modern statistical machine translation (SMT) systems usually use a linear combination of features to model the quality of each translation hypothesis. the linear combination assumes that all the features are in a linear relationship and constrains that each feature interacts with the rest features in an linear manner, which might limit the expressive power of the model and lead to a under-fit model on the current data. In this paper, we propose a non-linear modeling for the quality of translation hypotheses based on neural networks, which allows more complex interaction between features. A learning framework is presented for training the non-linear models. We also discuss possible heuristics in designing the network structure which may improve the non-linear learning performance. Experimental results show that with the basic features of a hierarchical phrase-based machine translation system, our method produce translations that are better than a linear model.

关键词： Computer aided language translation

来源：评论

学校读者我要写书评

暂无评论

Semi-supervised approach for Persian word sense disambiguation 7

Semi-supervised approach for Persian word sense disambiguati...

引用

7th international conference on Computer and Knowledge Engineering (ICCKE)

作者： Mahmoodvand, Mohamadreza Hourali, Maryam Malek Ashtar Univ Technol ICT Dept Tehran Iran

ISBN: (纸本)9781538608043

Word-sense disambiguation is one of the key concepts in natural language processing. the main goal of a language is to present a specific concept to the audience. this concept is extracted from the meaning of words in that language. System should be able to identify role and meaning of words in order to identify the concepts in texts properly. this issue becomes more problematic if there are words that take different meanings because of their surrounding words. Regarding that different practical programs have been developed in Persian language, it is vital now to find a solution for word-sense disambiguation in Persian language. Lack of training data is the biggest challenge in the course of word-sense disambiguation in Persian language. In order to face this problem, machine learning approach with minimal supervision is employed in this research. the applied method tries to disambiguate word senses by considering defined features of target words and applying collaborative learning method. Extracted corpus from published news by news agencies is used as the reference corpus. Evaluating the program by the available corpus on three considered ambiguous words, the implemented method has been able to properly identify the meaning of 5368 documents with 88% recall, 95% precision and 93% accuracy rate.

关键词： natural language processing Word Sense Disambiguation machine learning Semi-Supervised learning Text Mining

来源：评论

学校读者我要写书评

暂无评论

Research on Chinese Named Entity Recognition Methods for machine learning 7

Research on Chinese Named Entity Recognition Methods for Mac...

引用

7th international conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Ji, Ying Silc Business School Shanghai University Shanghai China

ISBN: (纸本)9798350361445

Named Entity Recognition (NER) is a crucial technology in natural language processing, and currently, deep learning-based methods have been widely applied to Chinese entity recognition research. For relevant articles in the field of machine learning, this article will use the Bert-BiLSTM-CRF model for key Chinese entity recognition. It first utilizes Bert pre trained language models based on the contextual information of characters to enhance the semantic vectors of characters. then input the output character vector sequence into the BiLSTM-CRF model for training. through experiments, the model is evaluated for the recognition of models, tools, techniques, and issues in the field of machine learning. the experimental results indicate that the model achieves a desirable level of accuracy. © 2024 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Joint Information Extraction and Reasoning: A Scalable Statistical Relational learning Approach 53

Joint Information Extraction and Reasoning: A Scalable Stati...

引用

作者： Wang, William Yang Cohen, William W. Carnegie Mellon Univ Language Technol Inst Pittsburgh PA 15213 USA Carnegie Mellon Univ Machine Learning Dept Pittsburgh PA 15213 USA

ISBN: (纸本)9781941643723

A standard pipeline for statistical relational learning involves two steps: one first constructs the knowledge base (KB) from text, and then performs the learning and reasoning tasks using probabilistic first-order logics. However, a key issue is that information extraction (IE) errors from text affect the quality of the KB, and propagate to the reasoning task. In this paper, we propose a statistical relational learning model for joint information extraction and reasoning. More specifically, we incorporate context-based entity extraction with structure learning (SL) in a scalable probabilistic logic framework. We then propose a latent context invention (LCI) approach to improve the performance. In experiments, we show that our approach outperforms state-of-the-art baselines over three real-world Wikipedia datasets from multiple domains;that joint learning and inference for IE and SL significantly improve both tasks;that latent context invention further improves the results.

关键词： Patents and inventions

来源：评论

学校读者我要写书评

暂无评论

learning Answer-Entailing Structures for machine Comprehension 53

Learning Answer-Entailing Structures for Machine Comprehensi...

引用

作者： Sachan, Mrinmaya Dubey, Avinava Xing, Eric P. Richardson, Matthew Carnegie Mellon Univ Pittsburgh PA 15213 USA Microsoft Res Redmond WA USA

ISBN: (纸本)9781941643723

Understanding open-domain text is one of the primary challenges in NLP machine comprehension evaluates the system's ability to understand text through a series of question-answering tasks on short pieces of text such that the correct answer can be found only in the given text. For this task, we posit that there is a hidden (latent) structure that explains the relation between the question, correct answer, and text. We call this the answer-entailing structure;given the structure, the correctness of the answer is evident. Since the structure is latent, it must be inferred. We present a unified max-margin framework that learns to find these hidden structures (given a corpus of question-answer pairs), and uses what it learns to answer machine comprehension questions on novel texts. We extend this framework to incorporate multi-task learning on the different subtasks that are required to perform machine comprehension. Evaluation on a publicly available dataset shows that our framework outperforms various IR and neural-network baselines, achieving an overall accuracy of 67.8% (vs. 59.9%, the best previously-published result.)

关键词： natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

An Empirical Study of Chinese Name Matching and Applications 53

An Empirical Study of Chinese Name Matching and Applications

引用

作者： Peng, Nanyun Yu, Mo Dredze, Mark Johns Hopkins Univ Human Language Technol Ctr Excellence Ctr Language & Speech Proc Baltimore MD 21218 USA Harbin Inst Technol Machine Intelligence & Translat Lab Harbin Heilongjiang Peoples R China

ISBN: (纸本)9781941643730

Methods for name matching, an important component to support downstream tasks such as entity linking and entity clustering, have focused on alphabetic languages, primarily English. In contrast, logogram languages such as Chinese remain untested. We evaluate methods for name matching in Chinese, including both string matching and learning approaches. Our approach, based on new representations for Chinese, improves both name matching and a downstream entity clustering task.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysis of Arabic Tweet Sentiment About Trending Hashtags Using Transfer learning and machine learning Models 7

Analysis of Arabic Tweet Sentiment About Trending Hashtags U...

引用

IEEE 7th international conference on Advanced Technologies, Signal and Image processing (ATSIP)

作者： Al-Qahtani, Waad Nasier Muniasamy, Anandhavalli King Khalid Univ Coll Comp Sci Abha Saudi Arabia

ISBN: (纸本)9798350351491;9798350351484

this study used a multi-pronged approach to examine how Gulf region Twitter users felt about COVID-19 trending topics. the data collection phase of the study started with the selection of relevant hashtags and time frames for analysis. the Twitter API was then used to compile a representative dataset of Arabic tweets pertaining to the COVID-19 trending topics. Subsequently, the research proceeded to the data annotation stage, employing a hybrid annotation technique that fused the transfer learning model and lexicon-based approach to assign a sentiment label to every tweet. Analyzing the patterns of tweet distribution over time exposed interesting patterns and possible sentiment expression influencers. the research obtained good accuracy scores by using a sentiment analysis model that combined three popular machine learning algorithms (Multinomial Naive Bayes, CountVectorizer, and TfidfVectorizer) with three feature representations (Ngram, TfidfVectorizer, and CountVectorizer). the sentiment tendencies of Arabic-speaking Twitter users toward trending topics were revealed by these scores. With the Ngram(1,2) representation, the LinearSVC algorithm achieved an impressive accuracy score of 89.1%, making it stand out as the best performer among all feature representations.

关键词： machine learning Opinion Mining Sentiment Analysis natural language processing Twitter Lexical Semantic Arabic language

来源：评论

学校读者我要写书评

暂无评论

Evaluating machine Translation Systems with Second language Proficiency Tests 53

Evaluating Machine Translation Systems with Second Language ...

引用

作者： Matsuzaki, Takuya Fujita, Akira Todo, Naoya Arai, Noriko H. Nagoya Univ Dept Elect Engn & Comp Sci Nagoya Aichi Japan Natl Inst Informat Informat & Soc Res Div Tokyo Japan

ISBN: (纸本)9781941643730

A lightweight, human-in-the-loop evaluation scheme for machine translation (MT) systems is proposed. It extrinsically evaluates MT systems using human subjects' scores on second language ability test problems that are machine-translated to the subjects' native language. A large-scale experiment involving 320 subjects revealed that the context-unawareness of the current MT systems severely damages human performance when solving the test problems, while one of the evaluated MT systems performed as good as a human translation produced in a context-unaware condition. An analysis of the experimental results showed that the extrinsic evaluation captured a different dimension of translation quality than that captured by manual and automatic intrinsic evaluation.

关键词： Quality control

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58页 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：