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

263 篇 会议
3 篇 期刊文献

馆藏范围

266 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

165 篇 工学
- 97 篇 计算机科学与技术...
- 77 篇 软件工程
- 34 篇 控制科学与工程
- 20 篇 机械工程
- 17 篇 仪器科学与技术
- 15 篇 电子科学与技术（可...
- 15 篇 网络空间安全
- 12 篇 信息与通信工程
- 4 篇 交通运输工程
- 3 篇 电气工程
- 3 篇 公安技术
- 1 篇 材料科学与工程（可...
- 1 篇 测绘科学与技术
- 1 篇 化学工程与技术
- 1 篇 地质资源与地质工...
- 1 篇 石油与天然气工程
66 篇 管理学
- 65 篇 管理科学与工程(可...
- 3 篇 工商管理
33 篇 理学
- 29 篇 系统科学
- 2 篇 大气科学
- 1 篇 地理学
- 1 篇 生物学
3 篇 经济学
- 3 篇 应用经济学
- 1 篇 理论经济学
3 篇 文学
- 2 篇 中国语言文学
- 1 篇 新闻传播学
3 篇 艺术学
- 3 篇 设计学（可授艺术学...
2 篇 法学
- 1 篇 法学
- 1 篇 社会学
1 篇 教育学
- 1 篇 教育学
1 篇 军事学

主题

10 篇 声学模型
10 篇 信息处理
7 篇 数据挖掘
7 篇 数据库
6 篇 预测模型
6 篇 测试数据压缩
5 篇 特征提取
5 篇 大数据处理
5 篇 信息安全
5 篇 深度学习
4 篇 大数据分析
4 篇 电话语音
4 篇 计算机网络
4 篇 网络安全
4 篇 异常检测
4 篇 卷积神经网络
3 篇 特征选择
3 篇 deep learning
3 篇 注意力机制
3 篇 支持向量机

机构

23 篇 清华大学
10 篇 合肥工业大学
6 篇 西北工业大学
5 篇 北方工业大学
4 篇 浙江大学
4 篇 中国科学技术大学
4 篇 山西大学
4 篇 东北大学
3 篇 中国科学院自动化...
3 篇 同济大学
3 篇 中国科学院计算技...
3 篇 阜阳师范学院
3 篇 山东大学
3 篇 school of comput...
3 篇 四川大学
3 篇 西安电子科技大学
3 篇 哈尔滨工业大学
3 篇 北京航空航天大学
3 篇 武汉大学
3 篇 贵州大学

作者

8 篇 梁华国
5 篇 王作英
5 篇 于志文
4 篇 徐波
4 篇 徐明星
3 篇 刘杰
3 篇 王海鹏
3 篇 郭斌
3 篇 苗启广
3 篇 江建慧
3 篇 王伟
3 篇 王国仁
3 篇 jin tang
3 篇 申国伟
3 篇 吴文虎
3 篇 易茂祥
3 篇 李晓维
2 篇 wenzhong wang
2 篇 黄正峰
2 篇 蔡莲红

语言

200 篇 中文
66 篇 英文

检索条件"任意字段=第六届中国计算机学会大数据学术会议"

共 266 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：

Virtual Machine Live Migration Strategy In Big Data Information System

Virtual Machine Live Migration Strategy In Big Data Informat...

引用

第六届中国计算机学会大数据学术会议

作者： Juan Fang Lifu Zhou Mengxuan Wang Faculty of Information Technology Beijing University of TechnologyBeijing 100022China

In recent years,as an emerging technology,cloud computing has pro-vided us with convenient services,and power consumption on issues have be-come increasingly *** machine live migration technology has be-come an important technology to reduce the power consumption of cloud com-puting *** the process of virtual machine migration,the performance of the virtual machine is inevitably degraded,which may violate service level agree-ment(SLA,Service Level Agreement).How to use virtual machine live migra-tion technology to reduce power consumption as much as possible while ensuring a low SLA violation rate becomes a hot *** paper aims to optimize the light load detection and virtual machine redistribution in the virtual machine live migration *** at the problem that the existing virtual machine light load detection method is easy to cause "over-migration",this paper proposes a threshold-based minimum CPU utilization method for light load detection,which effectively avoids excessive virtual machine *** at the problem that the current process of virtual machine re allocation algorithm is relatively simple,and there is a certain power loss space,we present power aware simula-tion annealing algorithm(PASA).The algorithm combines the simulated anneal-ing algorithm based on the power aware best fit decreasing algorithm(PABFD),which largely avoids the disadvantage that the PABFD easily falls into the local optimal solution *** paper uses the CloudSim simulator as simulation *** results show that compared with the best algorithm combination pro-posed by the previous researchers,the power consumption of the new algorithm combination proposed in the paper is reduced by 16.79%,and the SLA violation rate is reduced by 85.37%.Combining the two algorithms together can lead to better energy efficiency,performance and quality of service than using the two algorithms.

关键词： Cloud Computing Center Virtual Machine Migration Low Load Detection Algorithm Virtual Machine Reallocation Algorithm

来源：评论

学校读者我要写书评

暂无评论

Type Hierarchy Enhanced Heterogeneous Network Embedding for Fine-Grained Entity Typing in Knowledge Bases

Type Hierarchy Enhanced Heterogeneous Network Embedding for ...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Hailong Jin Lei Hou Juanzi Li Department of Computer Science and Technology Tsinghua University Beijing 100084China

ISBN: (纸本)9783030017156

Type information is very important in knowledge bases,but some large knowledge bases are lack of type information due to the incompleteness of knowledge *** this paper,we propose to use a well-defined taxonomy to help complete the type information in some knowledge ***,we present a novel embedding based hierarchical entity typing framework which uses learning to rank algorithm to enhance the performance of word-entity-type network *** this way,we can take full advantage of labeled and unlabeled *** experiments on two real-world datasets of DBpedia show that our proposed method significantly outperforms 4 state-of-the-art methods,with 2.8%and 4.2%improvement in Mi-F1 and Ma-F1 respectively.

关键词： Entity Typing Knowledge Base Completion Heterogeneous Network Embedding

来源：评论

学校读者我要写书评

暂无评论

End-to-end Task-Oriented Dialogue System with Distantly Supervised Knowledge Base Retriever

End-to-end Task-Oriented Dialogue System with Distantly Supe...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Libo Qin Yijia Liu Wanxiang Che Haoyang Wen Ting Liu Research Center for Social Computing and Information Retrieval Harbin Institute of Technology China

ISBN: (纸本)9783030017156

Task-oriented dialog systems usually face the challenge of querying knowledge ***,it usually cannot be explicitly modeled due to the lack of *** this paper,we introduce an explicit KB retrieval component(KB retriever)into the seq2seq dialogue *** first use the KB retriever to get the most relevant entry according to the dialogue history and KB,and then apply the copying mechanism to retrieve entities from the retrieved KB in decoding ***,the KB retriever is trained with distant supervision,which does not need any annotation *** on Stanford Multi-turn Task-oriented Dialogue Dataset shows that our framework significantly outperforms other sequence-to-sequence based baseline models on both automatic and human evaluation.

关键词： task-oriented dialog systems sequence-to-sequence Knowledge Base

来源：评论

学校读者我要写书评

暂无评论

A Study on Improving End-to-End Neural Coreference Resolution

A Study on Improving End-to-End Neural Coreference Resolutio...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Jia-Chen Gu Zhen-Hua Ling Nitin Indurkhya National Engineering Laboratory for Speech and Language Information Processing University of Science and Technology of ChinaHefeiChina

ISBN: (纸本)9783030017156

This paper studies the methods to improve end-to-end neural coreference ***,we introduce a coreference cluster modification algorithm,which can help modify the coreference cluster to rule out the dissimilar mention in the cluster and reduce errors caused by the global inconsistence of coreference ***,we tune the model from two aspects to get more accurate coreference resolution *** one hand,the simple scoring function is replaced with a feedforward neural network when computing the head word scores for later attention mechanism which can help pick out the most important *** the other hand,the maximum width of a mention is *** experimental results show that above methods improve the performance of coreference resolution effectively.

关键词： Coreference resolution End-to-end Neural network

来源：评论

学校读者我要写书评

暂无评论

Addressing Domain Adaptation for Chinese Word Segmentation with Instances-based Transfer Learning

Addressing Domain Adaptation for Chinese Word Segmentation w...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Yanna Zhang JinAn Xu Guoyi Miao Yufeng Chen Yujie Zhang School of Computer and Information Technology Beijing Jiaotong University

ISBN: (纸本)9783030017156

Recent studies have shown effectiveness in using neural networks for Chinese Word Segmentation(CWS).However,these models,constrained by the domain and size of the training corpus,do not work well in domain *** this paper,we propose a novel instance-transferring method,which use valuable target domain annotated instances to improve CWS on different ***,we introduce semantic similarity computation based on character-based n-gram embedding to select ***,training sentences similar to instances are used to help annotate *** results show that our method can effectively boost cross-domain segmentation *** achieve state-of-the-art results on Internet literatures datasets,and competitive results to the best reported on micro-blog datasets.

关键词： Chinese Word Segmentation Domain Adaptation Instance-Transferring Neural Network

来源：评论

学校读者我要写书评

暂无评论

Knowledge Graph Embedding with Logical Consistency

Knowledge Graph Embedding with Logical Consistency

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Jianfeng Du Kunxun Qi Yuming Shen Guangdong University of Foreign Studies Guangzhou 510006China

ISBN: (纸本)9783030017156

Existing methods for knowledge graph embedding do not ensure the high-rank triples predicted by themselves to be as consistent as possible with the logical background which is made up of a knowledge graph and a logical *** must take great effort to filter consistent triples before adding new triples to the knowledge *** alleviate users' burden,we propose an approach to enhancing existing embedding-based methods to encode logical consistency into the learnt distributed representation for the knowledge graph,enforcing high-rank new triples as consistent as *** evaluate this approach,four knowledge graphs with logical theories are constructed from the four great classical masterpieces of Chinese *** results on these datasets show that our approach is able to guarantee high-rank triples as consistent as possible while preserving a comparable performance as baseline methods in link prediction and triple classification.

关键词： logical Line graph Consistent Epistemology embedding Consumers baseline method Dataset

来源：评论

学校读者我要写书评

暂无评论

A Joint Model for Sentiment Classification and Opinion Words Extraction

A Joint Model for Sentiment Classification and Opinion Words...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Dawei Cong Jianhua Yuan Yanyan Zhao Bing Qin Research Center for Social Computing and Information Retrieval Harbin Institute of Technology China Department of Media Technology and Art Harbin Institute of TechnologyChina

ISBN: (纸本)9783030017156

In recent years,mining opinions from customer reviews has been widely ***-level sentiment analysis is a fine-grained subtask,which aims to detect the sentiment polarity towards a partic-ular target in a *** most previous works focus on senti-ment polarity classification,opinion words towards the target are also very important for that they provide details about target and contribute to judging *** this end,we propose a hierarchical network for jointly modeling aspect-level sentiment classification and word-level opin-ion words *** joint model acquires superior performance in opinion words extraction and achieves comparable results in sentiment polarity classification on two datasets from SemEval 2014.

关键词： aspect-level sentiment analysis opinion words extraction neural network attention mechanism

来源：评论

学校读者我要写书评

暂无评论

Medical Knowledge Attention Enhanced Neural Model for Named Entity Recognition in Chinese EMR

Medical Knowledge Attention Enhanced Neural Model for Named ...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Zhichang Zhang Yu Zhang Tong Zhou College of Computer Science and Engineering Northwest Normal UniversityChina

ISBN: (纸本)9783030017156

Named entity recognition(NER)in Chinese electronic medical records(EMRs)has become an important task of clinical natural language processing(NLP).However,limited studies have been performed on the clinical NER study in Chinese ***,when end-to-end neural network models have improved clinical NER performance,medical knowledge dictionaries such as various disease association dictionaries,which provide rich information of medical entities and relations among them,are rarely utilized in NER *** this study,we investigate the problem of NER in Chinese EMRs and propose a clinical neural network NER model enhanced with medical knowledge attention by combining the entity mention information contained in external medical knowledge bases with EMR context *** results on the manually labeled dataset demonstrated that the proposed method can achieve better performance than the previous methods in most cases.

关键词： Chinese Electronic Medical Record Named Entity Recognition Deep Learning Knowledge Attention

来源：评论

学校读者我要写书评

暂无评论

Linked Document Classification by Network Representation Learning

Linked Document Classification by Network Representation Lea...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Yue Zhang Liying Zhang Yao Liu Institute of Scientific and Technical Information of China BeijingChina School of Software and Micr Institute of Scientific and Technical Information of China BeijingChina

ISBN: (纸本)9783030017156

Network Representation Learning(NRL)can learn a latent space rep-resentation of each vertex in a topology network structure to reflect linked ***,NRL algorithms have been applied to obtain document embedding in linked document network,such as citation ***,most existing document representation methods with NRL are unsupervised and they cannot combine NRL with a concrete task-specific NLP *** in this paper,we propose a unified end-to-end hybrid Linked Document Classification(LDC)model which can capture semantic features and topological structure of documents to improve the performance of document *** addition,we investigate to use a more flexible strategy to capture structure similarity to improve the traditional rigid extraction of linked document topology *** experimental results suggest that our proposed model outperforms other document classification methods especially in the case of having less training sets.

关键词： Document Classification NRL Flexible Random Walk Strategy

来源：评论

学校读者我要写书评

暂无评论

Scientific Keyphrase Extraction:Extracting Candidates with Semi-supervised Data Augmentation

Scientific Keyphrase Extraction:Extracting Candidates with S...

引用

第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Qianying Liu Daisuke Kawahara Sujian Li School of Mathematical Science Peking University Graduate School of Informatics Kyoto UniversityJapan Key Laboratory of Computational Linguistics MOEPeking University

ISBN: (纸本)9783030017156

Keyphrase extraction can provide effective ways of organiz-ing scientific *** this task,neural-based methods usually suffer from performance unstability due to data *** this paper,we adopt the pipeline two-step method including candidate extraction and keyphrase ranking,where candidate extraction is a key to influence the whole *** the candidate extraction step,to overcome the low-recall problem of traditional rule-based method,we propose a novel semi-supervised data augmentation method,where a neural-based tagging model and a discriminative classifier boost each other and get more confident phrases as *** more reasonable candidates,keyphrase are identified with recall *** on SemEval 2017 Task 10 show that our model can achieve competitive results.

关键词： keyphrase extraction neural networks semi-supervised learning

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27页 << < 18 19 20 21 22 23 24 25 26 27 > >>

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：