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检索条件"机构=Services Computing Technology and System Lab"

共 568 条记录，以下是381-390 订阅

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Self-Adaptive Extracting Academic Entities from World Wide Web

Self-Adaptive Extracting Academic Entities from World Wide W...

引用

International Conference on Collaborative computing: Networking, Applications and Worksharing (CollaborateCom)

作者： Pingpeng Yuan Yi Li Hai Jin Ling Liu Services Computing Technology and System Lab. Huazhong University of Science and Technology Wuhan China Distributed Data Intensive Systems Lab. Georgia Institute of Technology Atlanta Georgia

Huge amount of entities and theirs relationships are posted on the Web. Those entities and theirs relationship networks help many activities. In this paper, we focus on the task of extracting academic entity network from homepages. Homepages usually contain many entities, such as persons, conference/journal and organization and theirs relationship. However, homepages don't follow a unified layout format and often contains similar information, but differs greatly in layouts and styles, which makes it impossible to use a unified set of rules to handle them all. Thus we propose an integrated approach to automatically extract data from unstructured texts. The main idea of the approach is to adopt the most suitable approach to extract entities. Thus, the approach is self-adaptive. Firstly, the approach decomposes web pages into text units and then classifier is used to determine units' type. Once the units' types are known, the different technologies are chosen to deal with them. For example, edit distance and inverted index are used to identify names etc. And Conditional Random Field technology is considered the best solution to extract publication entries. The result shows that LineX has achieved high performance on extracting entities from web pages in academic community.

关键词： Web pages Data mining Knowledge based systems Electronic mail HTML Internet Organizations

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Energy Minimization for Cellular Network Interfaces with Dynamic Link Quality

Energy Minimization for Cellular Network Interfaces with Dyn...

引用

International Conference on Computer Communications and Networks (ICCCN)

作者： Xiao Lei Zaiyang Tang Peng Li Hai Jin Song Guo Xiaofei Liao Feng Lu Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Aizu Daigaku Aizuwakamatsu Fukushima JP School of Computer Science and Engineering The University of Aizu Japan

It has been recognized that cellular network interfaces are not energy efficient because of tail energy after each transmission. Although many research efforts have been made to reduce tail energy, they ignore the dynamic of link quality caused by user mobility or network congestion, which would lead to limited improvement without quality-of-experience guarantee. In this paper, we study to minimize energy consumption of the cellular network interface with a sequence of download/upload requests. Given accurate estimation of achievable link rate, we design a dynamic-programming (DP) based algorithm to obtain the optimal solution. Without the knowledge of dynamic link quality and future requests, an online algorithm is proposed to approximate the optimal solution. Finally, we conduct extensive simulations using real traces to evaluate the performance of our proposals, and the results show that 29% energy can be saved by using our algorithm under typical network settings.

关键词： Heuristic algorithms Energy consumption Algorithm design and analysis Network interfaces Bandwidth Minimization Data communication

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Sparse Online Relative Similarity Learning

Sparse Online Relative Similarity Learning

引用

IEEE International Conference on Data Mining (ICDM)

作者： Dezhong Yao Peilin Zhao Chen Yu Hai Jin Bin Li Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China Data Analytics Department Institute for Infocomm Research Singapore Economics and Management School Wuhan University Wuhan China

ISBN: (纸本)9781467395052

For many data mining and machine learning tasks, the quality of a similarity measure is the key for their performance. To automatically find a good similarity measure from datasets, metric learning and similarity learning are proposed and studied extensively. Metric learning will learn a Mahalanobis distance based on positive semi-definite (PSD) matrix, to measure the distances between objectives, while similarity learning aims to directly learn a similarity function without PSD constraint so that it is more attractive. Most of the existing similarity learning algorithms are online similarity learning method, since online learning is more scalable than offline learning. However, most existing online similarity learning algorithms learn a full matrix with d 2 parameters, where d is the dimension of the instances. This is clearly inefficient for high dimensional tasks due to its high memory and computational complexity. To solve this issue, we introduce several Sparse Online Relative Similarity (SORS) learning algorithms, which learn a sparse model during the learning process, so that the memory and computational cost can be significantly reduced. We theoretically analyze the proposed algorithms, and evaluate them on some real-world high dimensional datasets. Encouraging empirical results demonstrate the advantages of our approach in terms of efficiency and efficacy.

关键词： Measurement Sparse matrices Image retrieval Machine learning algorithms Algorithm design and analysis Data mining Correlation

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One-Pass Anonymous Key Distribution in Batch for Secure Real-Time Mobile services

One-Pass Anonymous Key Distribution in Batch for Secure Real...

引用

IEEE International Conference on Mobile services (MS)

作者： Wei Wang Peng Xu Laurence Tianruo Yang Cyber-Physical-Social Systems Lab Huazhong University of Science and Technology Wuhan China Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China Department of Computer Science St. Francis Xavier University Canada

Key distribution is important to provide security guarantee for mobile services of Internet of Things (IoT). Traditional key distribution methods hardly provide single data server the promise to build multiple high-level secure real-time service channels simultaneously with high efficiency. In this paper we consider real-time data collecting or monitoring scenarios, which is commonly happened in health-care. In these scenarios, traditional key distribution approaches in public-key setting have difficulties on considering both security and efficiency during interactions. Besides, anonymity also shows importance during key distribution processes to keep personal privacy. In this paper we propose a secure real-time mobile service system and the corresponding security model, and novelly apply an Identity-Based Key Encapsulation Mechanism (IBKEM) in the proposed system as an instantiation that achieves one-pass anonymous key distribution in batch for mobile clients. The instantiated system shows both high-level security and efficiency in practice.

关键词： Mobile communication Real-time systems Protocols Cryptography Receivers Mobile computing

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MR-COF:A Genetic MapReduce Configuration Optimization Framework

MR-COF:A Genetic MapReduce Configuration Optimization Framew...

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The 7th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP2015(2015年第七届国际并行体系结构,算法和编程研讨会)

作者： Chao Liu Deze Zeng Hong Yao Chengyu Hu Xuesong Yan Yuanyuan Fan China Services Computing Technology and System Lab and Cluster and GridComputing Lab Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan 430074China

Hadoop/MapReduce has emerged as a de facto programming framework to explore cloud-computing *** has many configuration parameters,some of which are crucial to the performance of MapReduce *** practice,these parameters... 详细信息

ISBN: (纸本)9783319271392

关键词： Mapreduce Massive data processing Parameter configuration Performance optimization Search algorithm

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Boosting mapreduce with network-aware task assignment 4th

Boosting mapreduce with network-aware task assignment

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4th International Conference on Cloud computing, CloudComp 2013

作者： Xu, Fei Liu, Fangming Zhu, Dekang Jin, Hai Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319055053

Running MapReduce in a shared cluster has become a recent trend to process large-scale data analytical applications while improving the cluster utilization. However, the network sharing among various applications can make the network bandwidth for MapReduce applications constrained and heterogeneous. This further increases the severity of network hotspots in racks, and makes existing task assignment policies which focus on the data locality no longer effective. To deal with this issue, this paper develops a model to analyze the relationship between job completion time and the assignment of both map and reduce tasks across racks. We further design a network-aware task assignment strategy to shorten the completion time of MapReduce jobs in shared clusters. It integrates two simple yet effective greedy heuristics that minimize the completion time of map phase and reduce phase, respectively. With large-scale simulations driven by Facebook job traces, we demonstrate that the network-aware strategy can shorten the average completion time of MapReduce jobs, as compared to the state-of-the-art task assignment strategies, yet with an acceptable computational overhead. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.

关键词： MapReduce

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Automatic detection and recognition of silicosis in chest radiograph

Automatic detection and recognition of silicosis in chest ra...

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作者： Zhu, Lei Zheng, Ran Jin, Hai Zhang, Qin Zhang, Wei Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Silicosis remains one of the most harmful occupational respiratory diseases. It threatens the workers exposed to dust environment. Chest radiograph is the main available image source for silicosis diagnosis according to the diagnostic criteria of pneumoconiosis (DCP). Automatic detection and recognition of silicosis in chest radiograph has great importance on aiding the process of silicosis diagnosis. This paper proposes a multi-scale opacity detection approach to detect all suspected opacities from the chest radiograph. A support vector machine (SVM) based computer-aided silicosis diagnosis is proposed to recognize silicosis opacity from a large amount of candidate regions, and gives processing result for radiologist reference. Comprehensive experiments conducted on real world chest radiographs demonstrate that the proposed approach can reveal changes of silicosis pathology well, and it can be adopted as an effective tool for automatic silicosis diagnosis. © 2014 - IOS Press and the authors.

关键词： Support vector machines

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A novel clustered MongoDB-based storage system for unstructured data with high availability

A novel clustered MongoDB-based storage system for unstructu...

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作者： Jiang, Wenbin Zhang, Lei Liao, Xiaofei Jin, Hai Peng, Yaqiong Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

More and more unstructured data are produced and consumed over network. How to maintain these data and improve the availability and scalability of the storage systems has become a considerable challenge. Although some NoSQL systems such as Dynamo, Cassandra, MongoDB have provided different advantages for unstructured data management, no one can provide flexible query functions like MongoDB, meanwhile guarantee the availability and scalability as Cassandra simultaneously. This paper presents a new high available distributed storage system called MyStore based on an optimized clusteredMongoDB for unstructured data. Consistent hash is used to distribute data on multiple MongoDB nodes by applying virtual node method. NWR mode is applied to provide automatic backup operation and guarantee data consistency. And a gossip protocol is taken for exchanging information of failures in the system. Moreover, a user-friendly interface module and an efficient cache module are designed for improving the usability of the system. Based on above strategies, the system can realize high availability for unstructured data storage, while providing complex query functions like rational databases. Moreover, it is applied in a multi-discipline virtual experiment platform named VeePalms that has run practically. Experimental evaluation shows that the methodology is powerful enough not only to enhance the data availability, but also to improve the server's scalability. © Springer-Verlag Wien 2014.

关键词： Scalability

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Temporal-based ranking in heterogeneous networks

Temporal-based ranking in heterogeneous networks

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11th IFIP WG 10.3 International Conference on Network and Parallel computing, NPC 2014

作者： Yu, Chen Li, Ruidan Yao, Dezhong Lu, Feng Jin, Hai Services Computing Technology and System Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9783662449165

Ranking is a fundamental task for network analysis, benefiting to filter and find valuable information. Time information impacts results in content that is sensitive to trends and events ranking. The current ranking either assumes that user's interest and concerns remain static and never change over time or focuses on detecting recency information. Meanwhile most prevalent networks like social network are heterogeneous, that composed of multiple types of node and complex reliance structures. In this paper, we propose a general Temporal based Heterogeneous Ranking (TemporalHeteRank) method. We demonstrate that TemporalHeteRank is suitable for heterogeneous networks on the intuition that there is a mutually information balance relationship between different types of nodes that could be reflected on ranking results. We also explore the impact of node temporal feature in ranking, then we use the node life span by carefully investigating the issues of feasibility and generality. The experimental results on sina weibo ranking prove the effectiveness of our proposed approach. © 2014 IFIP International Federation for Information Processing.

关键词： Heterogeneous networks

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A real-time scheduling framework based on multi-core dynamic partitioning in virtualized environment

A real-time scheduling framework based on multi-core dynamic...

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11th IFIP WG 10.3 International Conference on Network and Parallel computing, NPC 2014

作者： Wu, Song Zhou, Like Fu, Danqing Jin, Hai Shi, Xuanhua Services Computing Technology and System Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9783662449165

With the prevalence of virtualization and cloud computing, many real-time applications are running in virtualized cloud environments. However, their performance cannot be guaranteed because current hypervisors' CPU schedulers aim to share CPU resources fairly and improve system throughput. They do not consider real-time constraints of these applications, which result in frequent deadline misses. In this paper, we present a real-time scheduling framework in virtualized environment. In the framework, we propose a mechanism called multi-core dynamic partitioning to divide physical CPUs (PCPUs) into two pools dynamically according to the scheduling parameters of real-time virtual machines (RT-VMs). We apply different schedulers to these pools to schedule RT-VMs and non-RT-VMs respectively. Besides, we design a global earliest deadline first (vGEDF) scheduler to schedule RT-VMs. We implement a prototype in the Xen hypervisor and conduct experiments to verify its effectiveness. © 2014 IFIP International Federation for Information Processing.

关键词： Virtualization

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