检索结果-内蒙古大学图书馆

2011 IEEE International Conference on Granular Computing, GrC 2011

作者： Wang, Shuliang International School of Software of Wuhan University Wuhan University Wuhan Hubei 430072 China Key Laboratory of Data Mining and Knowledge Engineering Hohhot China

ISBN: (纸本)9781457703713

Complex spatial data is the fundamental content of Smart Earth. Spatial data mining plays an important role in Smart Earth. In this paper, it is proposed that "Smart earth equals to Digital Earth plus the Internet of Things", which brings a new challenge for spatial data mining. First, the background of spatial data is summarized. Second, Smart Earth is put forward to be an integration of Digital Earth and the Internet of Things. Third, by analyzing the spatial data sources, types and structures, it uncovers that spatial data is the resource of Smart Earth. Fourth, spatial knowledge to discover in Smart Earth are analyzed on its connotations, extensions and categories. It indicates that spatial knowledge is the intelligent sources of Smart Earth. Fifth, based on spatial data characteristics and possible methodologies, the framework of spatial data mining is given under Smart Earth. Finally, the perspective of applicable fields is prospected for spatial data mining under Smart Earth. It is concluded that spatial data mining is one of the fundamental tools to achieve Smart Earth. © 2011 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

ALOR: Adaptive layout optimization of raft groups for heterogeneous distributed key-value stores 1

引用

15th IFIP International Conference on Network and Parallel Computing, NPC 2018

作者： Wang, Yangyang Chai, Yunpeng Wang, Xin Key Laboratory of Data Engineering and Knowledge Engineering MOE Beijing China School of Information Renmin University of China Beijing China College of Intelligence and Computing Tianjin University Tianjin China

ISBN: (数字)9783030056773

ISBN: (纸本)9783030056766

Many distributed key-value storage systems employ the simple and effective Raft protocol to ensure data consistency. They usually assume a homogeneous node hardware configuration for the underlying cluster and thus adopt even data distribution schemes. However, today’s distributed systems tend to be heterogeneous in nodes’ I/O devices due to the regular worn I/O device replacement and the emergence of expensive new storage media (e.g., non-volatile memory). In this paper, we propose a new data layout scheme called Adaptive Layout Optimization of Raft groups (ALOR), considering the hardware heterogeneity of the cluster. ALOR aims to optimize the data layout of Raft groups to achieve a better practical load balance, which leads to higher performance. ALOR consists of two components: leader migration in Raft groups and skewed data layout based on cold data migration. We conducted experiments on a practical heterogeneous cluster, and the results indicate that, on average, ALOR improves throughput by 36.89%, reduces latency and 99th percentile tail latency by 24.54% and 21.32%, respectively. © IFIP International Federation for Information Processing 2018.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

Extracting multi-records from web pages

Extracting multi-records from web pages

引用

4th International Conference on Semantics, knowledge, and Grid, SKG 2008

作者： Tian, Xia Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Resource Management Renmin University of China Beijing 100872 China

ISBN: (纸本)9780769534015

Extracting multi-records from web pages is useful, it allows us to integrate information from multiple sources to provide value-added services. Existing techniques still have some limitations because of their several restrictions and accuracy. This paper proposes a new method to perform multi-records extraction task automatically. Firstly, the HTML tag tree is build based on an embedded browser interface to solve the AJAX problem. Secondly, data regions are found out by data chunk comparison, and simple tree matching method is proposed to compute the chunk similarity. Finally, the main data region is determined and the multi-records are extracted out. Experimental results show that our method dramatically outperforms other existing methods, and it can extract multi-records from pages very accurately. © 2008 IEEE.

关键词： Websites

来源：评论

学校读者我要写书评

暂无评论

Visual group identification method of technical competitors using LinLog graph clustering algorithm

Visual group identification method of technical competitors ...

引用

IEEE International Conference on Computer Science and Automation engineering

作者： Han, Hong-Qi An, Xiaomi Zhu, Donghua Wang, Xuefeng Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Ministry of Education Beijing 100872 China School of Management and Economics Beijing Institute of Technology Beijing 100872 China

ISBN: (纸本)9781424487257

Visualization technique is a powerful method used by science and technology intelligence analysis experts to identify technical competitor groups. Common visualization methods tend to create graphs meeting the aesthetic criteria instead of finding better clusters, and their analysis results may provide misleading information. A process model of technical group identification method was presented using LinLog graph clustering algorithm to find better competitor groups. In the model, technical similarity value of each pair of competitors is measured based on their R&D output in sub-fields, and two competitors have a link when they have high similarity value;LinLog algorithm, which is aimed at producing better clusters, was employed to layout graph with competitors as nodes, their links as edges and technology similarity values as weights of edges. Experiment results show the efficiency of presented method. © 2011 IEEE.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Efficient querying of correlated uncertain data with cached results

Efficient querying of correlated uncertain data with cached ...

引用

18th International Conference on database Systems for Advanced Applications, DASFAA 2013

作者： Chen, Jinchuan Zhang, Min Xie, Xike Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China School of Information Renmin University of China China Department of Computer Science Aalborg University Denmark

ISBN: (纸本)9783642374869

Although there have been many efforts for management of uncertain data, evaluating probabilistic inference queries, a known NP-hard problem, is still a big challenge, especially for querying data with highly correlations. The state-of-art exact algorithms for accelerating the evaluation of inference queries are based on special indices. Besides, with the observation of the existence of many frequent queries, some researchers try to improve efficiency by reusing previously queried results. Indexing depends on the static properties like data distributions, whereas caching is in favor of the dynamic features like query workload. In this paper we propose a new approach for speeding up the evaluation of inference queries by caching frequent results in a junction tree-based hierarchical index. To the best of our knowledge, this is the first effort on utilizing both the static (data) and dynamic (query workload) properties to efficiently evaluate probabilistic inference queries. Moreover, according to our experience, different caching strategies may significantly affect the query performance. Basically a good caching strategy needs to have high cache hit ratio with limited space *** on these considerations, we propose a novel caching approach, called FVEC, and present corresponding algorithms for efficiently querying correlated uncertain data. We further conduct a series of extensive experiments on large uncertain datasets in order to illustrate the effectiveness and efficiency of our proposed approaches. As illustrated by the results, compared with previous solutions, our method could greatly improve the query performance. © Springer-Verlag 2013.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Distilling Dynamic Spatial Relation Network for Human Pose Estimation 32

Distilling Dynamic Spatial Relation Network for Human Pose E...

引用

32nd British Machine Vision Conference, BMVC 2021

作者： Wu, Kewei Wang, Tao Xie, Zhao Guo, Dan Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China

Human pose estimation is a challenging task that requires the comprehension of the pose structure. This work can refer to spatial relation inference in a pose structure model;how to model the dynamic spatial relation against various unreliable joints is critical. To this end, we propose a Distilling Dynamic Spatial Relation network (DDSR), which builds pose-based graph representation by exploiting the feature of spatial relation from the location distribution of joints. We use a dynamic message propagation mechanism to update the spatial relation on edges. Specifically, to filter out the noisy predictions, we select the joints with high confidence;to enhance the spatial relation in a large receptive field, we propagate multi-stage messages among joints. Besides, to reduce the computation cost of the multi-stage message propagation, we design a cross-resolution distillation framework. We use a new spatial distillation loss to verify the spatial relation between the teacher model and the student model. Experimental results on COCO and MPII datasets show that our method is superior to the state-of-the-art methods. The visualization results further verify the interpretability of our spatial relation. © 2021. The copyright of this document resides with its authors.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

Implementation and performance of VoIP interception based on SIP session border controller

Implementation and performance of VoIP interception based on...

引用

作者： Yang, Menghui Liu, Hua Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Resources Management Renmin University of China Beijing 100872 China

In an effort to provide lawful interception for session initiation protocol (SIP) voice over Internet protocol (VoIP), an interception architecture using session border controller (SBC) is proposed. Moreover, a prototype based on the proposed architecture is implemented. A testbed is set up and tests are carried out in order to analyze the performance and the capability of function entities and interfaces in the proposed architecture. Test results show that SBC interception capability in SIP signaling is superior to that in real-time transport protocol (RTP) media stream. In order to eliminate the possible bottleneck of RTP packets interception in SBC, an analytic model is proposed to investigate the mechanism in which RTP packet's traffics are shared among different SBC media functions. Analysis results show that multiple SBC media functions can share the RTP packets arrival and can significantly decrease RTP packets service time in SBC. Test results also show that delivery function, collect function and their interfaces in the proposed interception architecture have corresponding interception performance and capability with SBC. © 2013 Springer Science+Business Media New York.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

Learning Inter-Entity Interaction for Few-Shot knowledge Graph Completion

Learning Inter-Entity Interaction for Few-Shot Knowledge Gra...

引用

2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Li, Yuling Yu, Kui Huang, Xiaoling Zhang, Yuhong Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei China School of Computer Science and Information Enginerring Hefei University of Technology China

Few-shot knowledge graph completion (FKGC) aims to infer unknown fact triples of a relation using its few-shot reference entity pairs. Recent FKGC studies focus on learning semantic representations of entity pairs by separately encoding the neighborhoods of head and tail entities. Such practice, however, ignores the inter-entity interaction, resulting in low-discrimination representations for entity pairs, especially when these entity pairs are associated with 1-to-N, N-to-1, and N-to-N relations. To address this issue, this paper proposes a novel FKGC model, named Cross-Interaction Attention Network (CIAN) to investigate the inter-entity interaction between head and tail entities. Specifically, we first explore the interactions within entities by computing the attention between the task relation and each entity neighbor, and then model the interactions between head and tail entities by letting an entity to attend to the neighborhood of its paired entity. In this way, CIAN can figure out the relevant semantics between head and tail entities, thereby generating more discriminative representations for entity pairs. Extensive experiments on two public datasets show that CIAN outperforms several state-of-the-art methods. The source code is available at https://***/cjlyl/FKGC-CIAN. © 2022 Association for Computational Linguistics.

关键词： knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Electronic Medical Record Sharing System Based on Hyperledger Fabric and InterPlanetary File System 2021

Electronic Medical Record Sharing System Based on Hyperledge...

引用

5th International Conference on Compute and data Analysis, ICCDA 2021

作者： Li, Lei Yue, Zhengxiang Wu, Gongqing Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (纸本)9781450389112

Electronic Medical Records (EMR) and other medical data contain important and sensitive privacy information of patients, which provide important basis and reference for their doctors to diagnose and treat them. With the continuous development of data sharing, big data applications and other technologies, new requirements are proposed for the storage of medical privacy data. At present, medical data have the characteristics of obstructed sharing and exchange, difficult data tracing and data sensitivity, which increases the cost and difficulty of each diagnosis. Moreover, patients lack the right to know and control their own medical data, which is easy to cause data fraud or data leakage. As a decentralized, tamper proof and traceable distributed ledger system, blockchain brings new solutions to these problems. This paper designs a medical data fusion and distributed privacy management system based on the Hyperledger Fabric blockchain development platform and InterPlanetary File System. It can not only solve the problem of mutual distrust in the traditional system, but also realize the safe data storage and the safe sharing of medical record data between medical organizations which is a beneficial attempt to overcome the disadvantages of traditional hospital data separation. At the same time, according to the requirements of different levels and types of medical users or groups for data security and personal privacy protection, the access control technology of users is studied to ensure personal privacy data. © 2021 ACM.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

High-Dimensional Multi-Label data Stream Classification With Concept Drifting Detection

引用

IEEE Transactions on knowledge and data engineering 2023年第8期35卷 8085-8099页

作者： Li, Peipei Zhang, Haixiang Hu, Xuegang Wu, Xindong Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei230601 China Hefei University of Technology School of Computer Science and Information Engineering Hefei230601 China Second People's Hospital of Hefei Anhui Hefei230011 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of Education of China School of Computer Science and Information Engineering Anhui Hefei230002 China

Multi-label data streams such as Web texts and images have been popular on the Web. These data present the characteristics of multiple label, high dimensionality, high volume, high velocity and especial concept drift etc. Thus, multi-label data stream classification is a very challenging and significant task especially in the handling of high-dimensional data with concept drifts. However, this challenge has received little attention from the research community. Therefore, we propose the max-relevance and min-redundancy based algorithm adaptation approach for the efficient and effective classification on multi-label data streams with high-dimensional attributes and concept drifts. In order to reduce the impact from the high-dimensional data with noisy attributes, we first refine the minimal-redundancy-maximal-relevance criterion based on mutual information to select qualified features in multi-label data streams. Second, we propose the data distribution based concept drifting detection approach to distinguish concept drifts hidden in data streams. Finally, we build an incremental ensemble classification model for efficiently classifying multi-label data streams. Extensive studies show that our approach can get optimal subsets of features while maintaining a good performance in the multi-label classification, as compared to several state-of-the-art multi-label feature selection algorithms using two efficient multi-label classification methods as base classifiers. Meanwhile, our approach is superior to three well-known multi-label data stream classification approaches in the effectiveness and efficiency. © 1989-2012 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：