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International Conference on Advanced Information Networking and Applications Workshops (AINAW)

作者： Dexi Liu Changxuan Wan Naixue Xiong Jong Hyuk Park Sang-Soo Yeoe School of Information Technology Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China Department of Computer Science Georgia State University Atlanta GA USA Department of Computer Science and Engineering Seoul National University of Technology Seoul South Korea Division of Computer Engineering Mokwon University Daejeon South Korea

ISBN: (纸本)9781424467013;9780769540191

A Top-k aggregate query, which is a powerful technique when dealing with large quantity of data, ranks groups of tuples by their aggregate values and returns k groups with the highest aggregate values. However, compared to Top-k in traditional databases, queries over uncertain database are more complicated because of the existence of exponential possible worlds. As a powerful semantic of Top-k in uncertain database, Global Top-k return k highest-ranked tuples according to their probabilities of being in the Top-k answers in possible worlds. We propose a x-tuple based method to process Global Top-k aggregate queries in uncertain database. Our method has two levels, group state generation and G-x-Top-k query processing. In the former level, group states, which satisfy the properties of x-tuple, are generated one after the other according to their aggregate values, while in the latter level, dynamic programming based Global x-tuple Top-k query processing are employed to return the answers. Comprehensive experiments on different data sets demonstrate the effectiveness of the proposed solutions.

关键词： Aggregates databases knowledge engineering Query processing Computer networks Power engineering computing data engineering Power engineering and energy Dynamic programming Radar imaging

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Studies and implementation of the trusted process mechanism in a secure operating system

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Qinghua Daxue Xuebao/Journal of Tsinghua University 2010年第SUPPL. 1期50卷 1547-1553页

作者： Zhang, Chongbin Li, Fengjuan Liang, Bin China Information Technology Security Evaluation Center Beijing 100085 China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renming University of China Beijing 100872 China

The trusted process mechanism is an important part of the operating system security mechanism, but there is no uniform definition of the trusted process and there are some limitations in understanding its fundamental properties. In this paper, the trustworthiness of a trusted process is discussed in terms of privilege, data-operated integrity, functional and logic correctness, self-integrity, availability and trusted interactions. A trusted process definition is then given which summarizes the fundamental properties of a trusted process as a theoretical foundation for researching and enforcing the trusted process mechanism. A prototype of a trusted process mechanism is implemented in a secure operating system based on Linux, with the trustworthiness of the trusted process assured in many ways to improve and extende the original trust mechanisms in Linux.

关键词： Linux

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An Adaptive Method for the Efficient Similarity Calculation

An Adaptive Method for the Efficient Similarity Calculation

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14th International Conference on database Systems for Advanced Applications

作者： Cai, Yuanzhe Liu, Hongyan He, Jun Du, Xiaoyong Jia, Xu Key Labs of Data Engineering and Knowledge Engineering MOE China School of Information Renmin University of China China Department of Management Science and Engineering Tsinghua University China

ISBN: (纸本)9783642008863

SimRank is a well-known algorithm for similarity calculation based on object-to-object relationship. However, it suffers from high computation cost. Inthis paper, we find that the convergence behavior of different object pairs is different when we use SimRank to compute the similarity of objects. Many similarity scores converge fast, while others need more time before convergence. Based on this observation, we propose an adaptive method called Adaptive-SimRank to speed up similarity calculation. Using this method, we don't need to recalculate those converged pairs' similarity. The experiments conducted on web datasets and synthetic dataset show that our new method can reduce the running time by nearly 35%.

关键词： Similarity Calculation Linkage Mining

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Operating system mechanisms for TPM-based lifetime measurement of process integrity

Operating system mechanisms for TPM-based lifetime measureme...

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2009 IEEE 6th International Conference on Mobile Adhoc and Sensor Systems, MASS '09

作者： Xiao, Li Wenchang, Shi Zhaohui, Liang Bin, Liang Zhiyong, Shan Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University) Ministry of Education

ISBN: (纸本)9781424451135

Implementing runtime integrity measurement in an acceptable way is a big challenge. We tackle this challenge by developing a framework called Patos. This paper discusses the design and implementation concepts of our operating system mechanisms for runtime process integrity measurement, which is an important part of the Patos framework and is named Patos-RIP. Patos-RIP is developed into the mainstream Linux operating system and utilizes TPM as hardware support for tamper-resistance. From the beginning a process is created to the moment the process dies, Patos-RIP conducts integrity measurement at appropriate points of time when the process runs, so as to ensure that the integrity of a process is not compromised during its whole lifetime. This way, Patos-RIP can improve trustworthiness of processes by effectively detecting runtime tampering attacks on processes' integrity. ©2009 IEEE.

关键词： Computer operating systems

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Assessing the Influence Probability between Objects: A Random Walker Approach

Assessing the Influence Probability between Objects: A Rando...

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IEEE Symposium on Computational Intelligence and data Mining

作者： Li, Pei Li, Zhixu He, Jun Du, Xiaoyong Liu, Hongyan Key Labs of Data Engineering and Knowledge Engineering MOE China and School of Information Renmin University of China Beijing China Department of Management Science and Engineering Tsinghua University Beijing China

ISBN: (纸本)9781424427659

Influence between objects needs to be assessed in many applications. Lots of measures have been proposed, but a domain-independent method is still expected. In this paper, we give a probabilistic definition of influence based on the random walker model on graphs. Two approaches, linear systems method and Basic InfRank algorithm, are shown and return equal results, but Basic InfRank is more efficient by iterative computation. Two variants on bipartite graphs and star graphs are discussed. Experiments show InfRank algorithms have good accuracy, fast convergent rate and high performance.

关键词： Linear systems

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Median query research in wireless sensor networks

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2010年第2A期38卷 133-137页

作者： Wu, Zhong-Bo Zhang, Hui Chen, Hong Information School Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing 100872 China School of Mathematics and Computer Science Xiangfan University Xiangfan Hubei 441053 China

Poor quality and harsh condition can result in faulty and outlier data in sampling data of sensor nodes. So we need median query to reflect average level of monitoring region. First, we put forward HMA algorithm. Second, we extend HMA algorithm and put forward HFMA algorithm. In HFMA, We only need collect data inside filter and aggregate influence coefficient during sampling period. Base station can compute median result according to the sample data inside filter and influence coefficient aggregation value. Experimental results have shown that HFMA outperforms Naive algorithm and HMA algorithm and can prolong the lifetime of sensor network.

关键词： Sensor nodes

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Approximation algorithm for constructing data aggregation trees for wireless sensor networks

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中国高等学校学术文摘·计算机科学 2009年第4期3卷 524-534页

作者： Deying LI Jiannong CAO Qinghua ZHU Key Laboratory of Data Engineering and Knowledge Engineering School of InformationRenmin University of ChinaBeijing 100872China Internet and Mobile Computing Lab Department of ComputingHong Kong Polytechnic UniversityHong KongChina

This paper considers the problem of constructing data aggregation trees in wireless sensor networks (WSNs)for a group of sensor nodes to send collected information to a single sink *** data aggregation tree contains the sink node,all the source nodes,and some other non-source *** goal of constructing such a data aggregation tree is to minimize the number of non-source nodes to be included in the tree so as to save *** prove that the data aggregation tree problem is NP-hard and then propose an approximation algorithm with a performance ratio of four and a greedy *** also give a distributed version of the approximation *** simulations are performed to study the performance of the proposed *** results show that the proposed algorithms can find a tree of a good approximation to the optimal tree and has a high degree of scalability.

关键词： WSNs data aggregation tree approximation algorithm distributed algorithm

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Using link-based content analysis to measure document similarity effectively

Using link-based content analysis to measure document simila...

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Joint International Conference on Advances in data and Web Management, APWeb/WAIM 2009

作者： Li, Pei Li, Zhixu Liu, Hongyan He, Jun Du, Xiaoyong Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China Department of Management Science and Engineering Tsinghua University Beijing China

ISBN: (纸本)9783642006715

Along with a massive amount of information being placed online, it is a challenge to exploit the internal and external information of documents when assessing similarity between them. A variety of approaches have been proposed to model the document similarity based on different foundations, but usually they are not applicable for combining internal and external information. In this paper, we introduce a link-based method into content analysis, which is based on random walk on graphs. By defining similarity as the meeting probability of two random surfers, we propose a computational model for content analysis, which can also be integrated with external information of documents. Empirical study shows that our method achieves good accuracy, acceptable performance and fast convergent rate in multi-relational document similarity measuring. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Computers

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Exploiting the block structure of link graph for efficient similarity computation

Exploiting the block structure of link graph for efficient s...

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13th Pacific-Asia Conference on knowledge Discovery and data Mining, PAKDD 2009

作者： Pei, Li Yuanzhe, Cai Hongyan, Liu Jun, He Xiaoyong, Du Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China Department of Management Science and Engineering Tsinghua University Beijing China

ISBN: (纸本)3642013066

In many real-world domains, link graph is one of the most effective ways to model the relationships between objects. Measuring the similarity of objects in a link graph is studied by many researchers, but an effective and efficient method is still expected. Based on our observation of link graphs from real domains, we find the block structure naturally exists. We propose an algorithm called BlockSimRank, which partitions the link graph into blocks, and obtains similarity of each node-pair in the graph efficiently. Our method is based on random walk on two-layer model, with time complexity as low as O(n4/3) and less memory need. Experiments show that the accuracy of BlockSimRank is acceptable when the time cost is the lowest. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Artificial intelligence

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MrCAR: A Multi-relational Classification Algorithm based on Association Rules

MrCAR: A Multi-relational Classification Algorithm based on ...

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International Conference on Web Information Systems and Mining

作者： Gu, Yingqin Liu, Hongyan He, Jun Hu, Bo Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering MOE China Information School Renmin University of China Beijing 100872 China School of Economics and Management Tsinghua University Beijing 100084 China

ISBN: (纸本)9780769538174

Classification is an important subject in data mining and machine learning, which has been studied extensively and has a wide range of applications. Classification based on association rules is one of the most effective classification method, whose accuracy is higher and discovered rules are easier to understand comparing with classical classification methods. However, current algorithms for classification based on association rules is single table oriented, which means they can only apply to the data stored in a single relational table. Directly applying these algorithms in multi-relational data environment will result in many problems. This paper proposes a novel algorithm MrCAR for classification based on association rules in multi-relational data environment. MrCAR mines relevant features in each table to predict the class label. Close itemsets technique and Tuple ID Propagation method are used to improve the performance of the algorithm. Experimental results show that MrCAR has higher accuracy and better understandability comparing with a typical existing multirelational classification algorithm.

关键词： Association rules

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