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

806 篇 会议
791 篇 期刊文献

馆藏范围

1,597 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

985 篇 工学
- 708 篇 计算机科学与技术...
- 572 篇 软件工程
- 196 篇 信息与通信工程
- 135 篇 生物工程
- 115 篇 电气工程
- 114 篇 控制科学与工程
- 89 篇 电子科学与技术（可...
- 85 篇 光学工程
- 79 篇 生物医学工程（可授...
- 62 篇 机械工程
- 42 篇 化学工程与技术
- 41 篇 动力工程及工程热...
- 39 篇 仪器科学与技术
- 38 篇 交通运输工程
- 33 篇 建筑学
- 33 篇 土木工程
605 篇 理学
- 310 篇 数学
- 170 篇 物理学
- 151 篇 生物学
- 98 篇 统计学（可授理学、...
- 49 篇 化学
- 49 篇 系统科学
- 41 篇 地球物理学
246 篇 管理学
- 145 篇 管理科学与工程(可...
- 115 篇 图书情报与档案管...
- 49 篇 工商管理
63 篇 医学
- 53 篇 临床医学
- 45 篇 基础医学(可授医学...
- 32 篇 药学(可授医学、理...
49 篇 法学
- 39 篇 社会学
21 篇 经济学
15 篇 农学
7 篇 教育学
3 篇 艺术学
2 篇 文学
2 篇 军事学

主题

63 篇 feature extracti...
58 篇 semantics
47 篇 training
45 篇 computational mo...
37 篇 deep learning
37 篇 machine learning
35 篇 graph neural net...
35 篇 accuracy
34 篇 predictive model...
34 篇 data models
25 篇 convolution
24 篇 task analysis
23 篇 image segmentati...
22 篇 federated learni...
19 篇 deep neural netw...
19 篇 neural networks
18 篇 memory managemen...
18 篇 cloud computing
17 篇 data mining
16 篇 topology

机构

214 篇 beijing advanced...
102 篇 national enginee...
66 篇 school of comput...
63 篇 beijing advanced...
58 篇 shandong provinc...
53 篇 school of cyber ...
50 篇 key laboratory o...
46 篇 shandong enginee...
40 篇 national enginee...
39 篇 school of comput...
33 篇 hubei engineerin...
32 篇 services computi...
29 篇 cluster and grid...
28 篇 hubei key labora...
27 篇 huazhong univers...
23 篇 university of ch...
23 篇 school of econom...
22 篇 school of softwa...
21 篇 engineering rese...
21 篇 guangxi cooperat...

作者

127 篇 hai jin
122 篇 jin hai
43 篇 xiaofei liao
42 篇 li jianxin
41 篇 peng hao
25 篇 hu shengshan
22 篇 long zheng
22 篇 corianò claudio
22 篇 liao xiaofei
21 篇 haikun liu
21 篇 yu philip s.
20 篇 xiwang dong
20 篇 zhang ren
20 篇 zhao weisheng
19 篇 qingdong li
18 篇 yu zhang
17 篇 zou deqing
17 篇 zhang leo yu
16 篇 lionetti stefano
15 篇 li qian

语言

1,462 篇 英文
120 篇 其他
35 篇 中文

检索条件"机构=Big Data Computing Center"

共 1597 条记录，以下是81-90 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：

POINE2: Improving Poincaré Embeddings for Hierarchy-Aware Complex Query Reasoning over Knowledge Graphs 26

POINE2: Improving Poincaré Embeddings for Hierarchy-Aware C...

引用

26th European Conference on Artificial Intelligence, ECAI 2023

作者： Liu, Junnan Mao, Qianren Li, Jianxin Fu, Xingcheng Wang, Zheng School of Computer Science and Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing China Zhongguancun Laboratory Beijing China The School of Computing University of Leeds United Kingdom

ISBN: (纸本)9781643684369

Reasoning complex logical queries on incomplete and massive knowledge graphs (KGs) remains a significant challenge. The prevailing method for this problem is query embedding, which embeds KG units (i.e., entities and relations) and complex queries into low-dimensional space. Recent developments in the field show that embedding queries as geometric shapes is a viable means for modeling entity set and logical relationships between them. Despite being promising, current geometric-based methods face challenges in capturing hierarchical structures of complex queries, which leaves considerable room for improvement. This paper presents POINE2, a geometric-based query embedding framework based on hyperbolic geometry to handle complex queries on knowledge graphs. POINE2 maps entities and queries as geometric shapes on a Cartesian product space of Poincaré ball spaces. To capture the hierarchical structures of complex queries, we use the Poincaré radius to represent the different levels of the hierarchy, and we use the aperture of the shape to indicate semantic differences at the same level of the hierarchy. Additionally, POINE2 offers a flexible and expressive definition of logical operations. Experimental results show that POINE2 outperforms existing salient geometric-based embedding methods and significantly improves these methods on evaluation datasets. © 2023 The Authors.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Large Language Model Based on Full-Text Retrieval for Temporal Knowledge Q&A Approach

Large Language Model Based on Full-Text Retrieval for Tempor...

引用

Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Zhidong Li Licai Wang Qibin Luo Silong Qiao Big data research and development center North China Institute of Computing Technology Beijing China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

Knowledge Q&A is one of the hot research topics in the field of natural language processing, and temporal knowledge Q&A is a difficult area of Q&A reasoning because it also needs to consider the temporal relationship of knowledge. Today's research usually focuses on the word vector similarity between knowledge and questions as an important basis for answering, while ignoring the sentence granularity semantic information embedded in the knowledge. In this paper, we propose a method of temporal knowledge Q&A for large language models based on full-text retrieval, firstly, the sentence granularity knowledge recall is performed by Elasticsearch so that large language models can learn the knowledge that is highly relevant to the problem, and then verify the temporal knowledge Q&A ability of large language models under Zero-shot, One-shot and Few-shot. The experiments were conducted on the ICEWS05-15 dataset, and the accuracy of answers was significantly improved, demonstrating the effectiveness of the temporal knowledge Q&A method for large language models based on Elasticsearch.

关键词： Seminars Knowledge engineering Accuracy Large language models Semantics Knowledge graphs Vectors

来源：评论

学校读者我要写书评

暂无评论

Legal Event Detection Model Based on ERNIE 3.0-CRF and Ensemble Learning

Legal Event Detection Model Based on ERNIE 3.0-CRF and Ensem...

引用

Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Siyu Wang Licai Wang Ke Zhang Big data research and development center North China Institute of Computing Technology Beijing China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

Recognizing events is a prerequisite for making judgments, so discovering events in legal documents is important for the analysis of legal case. Legal Event Detection aims to extract legal event trigger words from legal documents and categorize events and is the basis of many judicial AI applications. Oriented to the needs of understanding and analyzing legal events in the judicial trial process, and in response to the low accuracy of event detection caused by the many types of events and little sample data in the legal domain, this paper constructs a pre-training model oriented to event detection in the legal domain, which makes full use of ERNIE 3.0's powerful semantic representation learning capability and CRF's effective modeling capability for sequence annotation tasks. In addition, we further enhance the effectiveness of the model through data augmentation and ensemble learning. The experimental results show that the method works better compared to the baseline model and improves the prediction accuracy of legal event detection.

关键词： Seminars Analytical models Accuracy Law Event detection Predictive models data models

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Based Multi-Cloud data Storage System Disaster Recovery

Blockchain-Based Multi-Cloud Data Storage System Disaster Re...

引用

2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Wang, Feiyu Zhou, Jian-Tao College of Computer Science Inner Mongolia University Inner Mongolia Hohhot China Engineering Research Center of Ecological Big Data Ministry of Education Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Inner Mongolia Key Laboratory of Social Computing and Data Processing Inner Mongolia Engineering Laboratory for Big Data Analysis Technology China

ISBN: (纸本)9798350337020

Cloud storage services have been used by most businesses and individual users. However, data loss, service interruptions and cyber attacks often lead to cloud storage services not being provided properly, and these incidents have caused financial losses to users. Second, traditional and single-cloud model disaster recovery services are no longer suitable for the current complex cloud storage systems. Therefore, a scheme to provide disaster recovery for cloud storage services in a multi-cloud storage environment is needed in real production. In this paper, we propose a disaster recovery scheme based on blockchain technology. The proposed scheme outlined in this study aims to address the issue of data availability within the cloud storage landscape. The proposed scheme achieves this goal by dividing data into hot and cold categories, verifying the integrity of copy data via blockchain technology, and utilizing blockchain networks to manage multi-cloud storage systems. Experimental findings demonstrate that the proposed scheme yields superior results in terms of computation and time overheads. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

RIF-Proto: A Few-Shot Relation Extraction for Prototype Networks Based on Relational Information Features

RIF-Proto: A Few-Shot Relation Extraction for Prototype Netw...

引用

Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Shuai Zhang Licai Wang Yangchen Huang Big data research and development center North China Institute of Computing Technology Beijing China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

Relation extraction stands as a core task within the realm of information extraction, focusing on identifying the target relations between entities in text. While traditional relation extraction has been extensively researched, certain relations lack sufficient labeled data, rendering traditional models ineffective in practical research. Hence, the research focus in this field has shifted towards few-shot learning methods that leverage limited labeled data for training. Significant progress has been made in few-shot relation extraction, with prototype networks garnering attention from scholars for their outstanding performance in few-shot tasks. Prototype networks utilize the clustering idea to achieve relationship classification simply and efficiently, and their training process is mainly divided into three parts: generation of relationship prototypes, relationship classification, and loss calculation. The majority of current research is centered around leveraging external information to enhance the generation of prototypes and loss functions, but due to the difficulty of obtaining external data and the high complexity of data processing, it greatly increases the time cost and the difficulty of implementation. Given the aforementioned challenges, this paper introduces a method for prototype refinement leveraging relationship similarity among existing data. This approach aims to effectively address the issue of significant deviations in relationship prototypes. Initially, extract relationship vectors from the instances in both the support set and query set, followed by computing the relationship similarity between samples based on these vectors, and finally, this paper constructs a prototype correction module, which utilizes the relationship similarity to assign weights to the samples in the support set, to achieve the purpose of prototype correction. In the experiments against the standard dataset FewRel1.0., we observe that the method substantially improves the ex

关键词： Training Seminars Semantics Prototypes Feature extraction Rendering (computer graphics) Vectors

来源：评论

学校读者我要写书评

暂无评论

BMDP:Blockchain-Based Multi-Cloud Storage data Provenance 26

BMDP:Blockchain-Based Multi-Cloud Storage Data Provenance

引用

26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wang, Feiyu Zhou, Jian-Tao Guo, Xu Inner Mongolia University College of Computer Science Inner Mongolia Hohhot China Inner Mongolia Key Laboratory of Social Computing and Data Processing Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Engineering Research Center of Ecological Big Data Ministry of Education Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software China

ISBN: (纸本)9798350331684

In a multi-cloud storage system, provenance data records all operations and ownership during its lifecycle, which is critical for data security and audibility. However, recording provenance data also poses some challenging security and storage issues. In this paper, we present a secure and efficient multi-cloud storage data source scheme, BMDP. We use blockchain technology to ensure the secure storage of provenance data and design a smart contract to utilize the provenance data to ensure the proper operation of the multi-cloud storage system. Finally, we analyze the scheme's safety and do simulation experiments to show that the scheme has practicality. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Fast Parallel Recovery for Transactional Stream Processing on Multicores 40

Fast Parallel Recovery for Transactional Stream Processing o...

引用

40th IEEE International Conference on data Engineering, ICDE 2024

作者： Zhao, Jianjun Liu, Haikun Zhang, Shuhao Duan, Zhuohui Liao, Xiaofei Jin, Hai Zhang, Yu School of Computer Science and Technology Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan China School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798350317152

Transactional stream processing engines (TSPEs) have gained increasing attention due to their capability of processing real-time stream applications with transactional semantics. However, TSPEs remain susceptible to system failures and power outages. Existing TSPEs mainly focus on performance improvement, but still face a significant challenge to guarantee fault tolerance while offering high-performance services. We revisit commonly-used fault tolerance approaches in stream processing and database systems, and find that these approaches do not work well on TSPEs due to complex data dependencies. In this paper, we propose a novel TSPE called MorphStreamR to achieve fast failure recovery while guaranteeing low performance overhead at runtime. The key idea of MorphStreamR is to record intermediate results of resolved dependencies at runtime, and thus eliminate data dependencies to improve task parallelism during failure recovery. MorphStreamR further mitigates the runtime overhead by selectively tracking data dependencies and incorporating workload-aware log commitment. Experimental results show that MorphStreamR can significantly reduce the recovery time by up to 3.1 x while experiencing much less performance slowdown at runtime, compared with other applicable fault tolerance approaches. © 2024 IEEE.

关键词： Fault tolerance

来源：评论

学校读者我要写书评

暂无评论

Analysis on n-level quantum systems by means of a coordinate transformation 63

Analysis on n-level quantum systems by means of a coordinate...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Xu, Huilong Miao, Zibo Gao, Qing Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University School of Automation Science and Electrical Engineering Beijing100191 China

ISBN: (纸本)9798350316339

The structural decomposition of two-level quantum systems has recently been established, related to various applications in quantum information science. As an extension to previous work on two-level quantum systems, this paper aims to investigate the structural properties of n-level quantum systems. We develop algebraic conditions under which the attainment of quantum back-action evading (BAE) measurements, the generation of decoherence-free (DF) subspaces and quantum non-demolition (QND) variables, as well as the existence of steadystate solutions for the Lindblad equations, can be realized. In particular, a specific coordinate transformation is explicitly constructed to facilitate the achievement of above-mentioned objectives, accompanied by an illustrative numerical example. © 2024 IEEE.

关键词： Quantum optics

来源：评论

学校读者我要写书评

暂无评论

Machine Learning is All You Need: A Simple Token-Based Approach for Effective Code Clone Detection 24

Machine Learning is All You Need: A Simple Token-Based Appro...

引用

44th ACM/IEEE International Conference on Software Engineering, ICSE 2024

作者： Feng, Siyue Suo, Wenqi Wu, Yueming Zou, Deqing Liu, Yang Jin, Hai Huazhong University of Science and Technology China Nanyang Technological University Singapore Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Jinyinhu Laboratory Wuhan430074 China School of Cyber Science and Engineering Hust Wuhan430074 China School of Computer Science and Technology Hust Wuhan430074 China

ISBN: (纸本)9798400702174

As software engineering advances and the code demand rises, the prevalence of code clones has increased. This phenomenon poses risks like vulnerability propagation, underscoring the growing importance of code clone detection techniques. While numerous code clone detection methods have been proposed, they often fall short in real-world code environments. They either struggle to identify code clones effectively or demand substantial time and computational resources to handle complex clones. This paper introduces a code clone detection method namely Toma using tokens and machine learning. Specifically, we extract token type sequences and employ six similarity calculation methods to generate feature vectors. These vectors are then input into a trained machine learning model for classification. To evaluate the effectiveness and scalability of Toma, we conduct experiments on the widely used bigCloneBench dataset. Results show that our tool outperforms token-based code clone detectors and most tree-based clone detectors, demonstrating high effectiveness and significant time savings. © 2024 ACM.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need 38

Unlearnable 3D Point Clouds: Class-wise Transformation Is Al...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Wang, Xianlong Li, Minghui Liu, Wei Zhang, Hangtao Hu, Shengshan Zhang, Yechao Zhou, Ziqi Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity information, unauthorized usage of this new type data has also become a serious concern. To address this, we propose the first integral unlearnable framework for 3D point clouds including two processes: (i) we propose an unlearnable data protection scheme, involving a class-wise setting established by a category-adaptive allocation strategy and multi-transformations assigned to samples;(ii) we propose a data restoration scheme that utilizes class-wise inverse matrix transformation, thus enabling authorized-only training for unlearnable data. This restoration process is a practical issue overlooked in most existing unlearnable literature, i.e., even authorized users struggle to gain knowledge from 3D unlearnable data. Both theoretical and empirical results (including 6 datasets, 16 models, and 2 tasks) demonstrate the effectiveness of our proposed unlearnable framework. Our code is available at https://***/CGCL-codes/UnlearnablePC. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

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160页 << < 5 6 7 8 9 10 11 12 13 14 > >>

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：