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A community detection method to undirected weighted signed social networks

Journal of Computational Information Systems 2015年第10期11卷 3623-3632页

作者： Guo, Jingfeng Liu, Miaomiao Liu, Linlin Liu, Yuanying College of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China Northeast Petroleum University Daqing China

With regard to the community mining in weighted signed networks and weighted social networks containing only positive links, the AGMA algorithm has some imperfections in the second clustering of vertices. So some improvements were made to it. And a new algorithm CD WSSN (Community Detection for Weighted Signed Social Networks) is proposed to detect communities in undirected and unweighted signed networks. It takes the sign of the edge, the weight of the edge and the friend coefficient between the vertex and community as clustering criteria of vertices. It can divide a weighted signed network into the right number of communities accurately and effectively. Experiments were done on datasets like weighted signed networks, weighted traditional social networks, unweighted signed networks as well as standard networks. The comparative analysis of the experimental results were also done with regard to the difference and frustration about CD WSSN, AGMA, CRA algorithm, and so on. The results verify the accuracy and generality of the algorithm. ©, 2015, Binary Information Press. All right reserved.

关键词： Population dynamics

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Mining important nodes in directed-weighted software network based on semi-global structure information

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ICIC Express Letters 2015年第10期9卷 2859-2866页

作者： Ren, Jiadong Wu, Hongfei Yin, Tengteng Liu, Yang He, Haitao College of Information Science and Engineering Yanshan University No. 438 West Hebei Ave. Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 West Hebei Ave. Qinhuangdao China

Software’s control flow graph can be treated as a complex software network, and a tiny fraction of key function nodes has considerable influence on the stability, reliability and robustness of the network. Identifying the top-k key nodes accurately and effectively has become an important topic in software engineering. In this paper, directedweighted function dependency network (DWFDN) is adopted to represent the function and relationship of function calling or dependency. The weight on a direct edge indicates the frequency of function calling. Weighted semi-global structure information (the weight, the relative position of a function node and the topological structure among its neighbor nodes) is taken into consideration in our approach. From the perspective of accumulating and propagating vulnerabilities, key function callers and function callees are mined respectively. Case studies on real software date show the utility of the approach. © 2015, ICIC International.

关键词： Software reliability

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Towards Constant-Time Cardinality Estimation for Large-Scale RFID Systems

Towards Constant-Time Cardinality Estimation for Large-Scale...

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International Conference on Parallel Processing (ICPP)

作者： Binbin Li Yuan He Wenyuan Liu School of Information Science and Engineering YanShan University China TNLIST Tsinghua University China The Key Laboratory for Computer Virtual Technology System Integration of HeBei Province China

ISBN: (纸本)9781467375887

Cardinality estimation is the process to survey the quantity of tags in a RFID system. Generally, the cardinality is estimated by exchanging information between reader(s) and tags. To ensure the time efficiency and accuracy of estimation, numerous probability-based approaches have been proposed, most of which follow a similar way of minimizing the number of required time slots from tags to reader. The overall execution time of the estimator, however, is not necessarily minimized. The estimation accuracy of those approaches also largely depends on the repeated rounds, leading to a dilemma of choosing efficiency or accuracy. In this paper, we propose BFCE, a Bloom Filter based Cardinality Estimator, which only needs a constant number of time slots to meet desired estimation accuracy, regardless of the actual tag cardinality. The overall communication overhead is also significantly cut down, as the reader only needs to broadcast a constant number of messages for parameter setting. Results from extensive simulations under various tag IDs distributions shows that BFCE is accurate and highly efficient. In terms of the overall execution time, BFCE is 30 times faster than ZOE and 2 times faster than SRC in average, the two state-of-the-arts estimation approaches.

关键词： Estimation Radiofrequency identification Servers Probabilistic logic Protocols Approximation methods Error probability

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A novel hierarchical clustering method in signed social network

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Journal of Computational Information Systems 2015年第21期11卷 7865-7872页

作者： Guo, Jingfeng Chen, Xiao Fan, Chaozhi Hu, Xinzhuan College of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China Qian'an College North China University of Science and Technology Qian'an China

Based on a new feature that macro network structure and micro game have mutual inuence on the formation of the community, to mining communities in signed network, a novel algorithm SNCGHC is proposed. Firstly, according to the signed attributes and the node degree, the Shapley Value is improved, to avoid ignoring the effect of external environment on the Shapley Value and reduce the calculation complexity. Secondly, considering the inuence of network density on the formation of the coalition (community), we find the calculation method of average coalition payoff and create the signed network coalitional game model. Thirdly, SNCGHC depends on average payoff maximization of coalition to achieve hierarchical clustering of signed network. Finally, experiments show that our method can detect better community structures as compared to other existing methods. Copyright © 2015 Binary Information Press.

关键词： Game theory

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ICRA: An improved community detection algorithm on signed social networks

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Journal of Computational Information Systems 2015年第11期11卷 4091-4099页

作者： Hu, Xinzhuan Guo, Jingfeng Zhao, Yue Liu, Yuanying School of Economics and Management Yanshan University Qinhuangdao China College of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

The study on signed social networks community detection has been paid more and more attention. Research shows that two-phase signed social networks community detection algorithm can not correctly divide the network. To solve the problem, we propose a new algorithm: ICRA (Improved Clustering Re-clustering Algorithm). In the process of community division, the assignment of vertices with negative edges shall be determined by comparing the value of network positive density with community positive density. Our algorithm solves the problems existing in CRA, including network division failure and wrong division starting from different vertices. ©, 2015, Binary Information Press. All right reserved.

关键词： Clustering algorithms

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Mining weighted frequent traversal pattern from software executing graph

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ICIC Express Letters 2015年第11期9卷 2893-2900页

作者： He, Haitao Yin, Tengteng Pei, Caiyan Wu, Hongfei Ren, Jiadong College of Information Science and Engineering No. 438 West Hebei Ave. Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 West Hebei Ave. Qinhuangdao China School of Mathematics and Information Science and Technology Hebei Normal University of Science and Technology No. 360 West Hebei Street Qinhuangdao China

Mining important patterns in complex software executing network plays an important role in analyzing software security. The general sequential pattern mining algorithms may lead to poor performance due to the lack of consideration on the continuous property of software path traversals and the different importance of functions. To address the issue, a novel approach called weighted frequent traversal pattern miner (WFTPMiner) to mine weighted frequent traversal pattern from software executing graph is presented in this paper. In WFTPMiner, weighted software executing graph (WSEG) is modeled firstly. Secondly, software path traversals are extracted from WSEG by depthfirst- search (DFS) strategy. Thirdly, according to continuity characteristics of software path traversals, a potential frequent suffix sequence tree (PFSS-Tree) is defined to store the potential weighted frequent traversal patterns. A pruning strategy is adopted by PFSSTree. The pruning strategy can prune infrequent patterns effectively. The experimental results show that WFTPMiner has better efficiency compared with some previous algorithms. © 2015 ICIC International.

关键词： Forestry

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The constructions of ternary sequence pairs with two-level autocorrelation

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Journal of Information and Computational Science 2014年第13期11卷 4605-4612页

作者： Jia, Yanguo Duan, Xiaobei Shi, Yan Shen, Xiumin Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province School of Information Science and Engineering Yanshan University Qinhuangdao China

In this letter, a periodic autocorrelation signal is presented, which is the ternary sequence pair with two-level autocorrelation. The methods of constructing ternary sequence pairs based on binary sequence pairs and cyclotomy are presented by us. Then we have a discussion about perfect binary sequence pairs, pseudorandom binary sequence pairs, difference set pairs and ternary sequence pairs. These signals enrich the theory of sequence pair discrete correlation signals. Copyright © 2014 Binary Information Press.

关键词： Autocorrelation

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The study of a hierarchical hadoop architecture in multiple data centers environment

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Open Cybernetics and Systemics Journal 2015年第1期9卷 131-137页

作者： Shengtao, Sun Aizhi, Wu Xiaoyang, Liu School of Information Science and Engineering Yanshan University QinhuangdaoHebei066004 China College of Vehicles and Energy Yanshan University QinhuangdaoHebei066004 China Data Industry Research Institute Limited Company QinhuangdaoHebei066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province QinhuangdaoHebei066004 China

Hadoop is a reasonable tool for cloud computing in big data era and MapReduce paradigm may be a highly successful programming model for large-scale data-intensive computing application, but the conventional MapReduce model and Hadoop framework limit themselves to implement jobs within single cluster. Traditional single-cluster Hadoop may not suitable for situations when data and compute resources are widely distributed this paper focuses on the application of Hadoop across multiple data centers and clusters. A hierarchical distributed computing architecture of Hadoop is designed and the virtual Hadoop file system is proposed to provide global data view across multiple data centers. The job submitted by user can be decomposed automatically into several sub-jobs which are then allocated and executed on corresponding clusters by location-aware manner. The prototype based on this architecture shows encouraging results. © Shengtao et al.

关键词： MapReduce

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New construction of quaternary sequence pairs with even period

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Journal of Information and Computational Science 2014年第13期11卷 4613-4621页

作者： Jia, Yanguo Shi, Yan Duan, Xiaobei Shen, Xiumin Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province School of Information Science and Engineering Yanshan University Qinhuangdao China

In the paper, we present a new method for constructing a class of quaternary sequence pairs with even period 2N from the known binary sequence pairs with odd period N by using the reverse Gray mapping and interleaving technique. The distribution of correlation function of the proposed quaternary sequence pairs is also derived, which is decided by the properties and the periods of the known binary sequence pairs. Copyright © 2014 Binary Information Press.

关键词： Mapping

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Robust recommendation algorithm based on the identification of suspicious users and matrix factorization

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Journal of Information and Computational Science 2014年第13期11卷 4769-4777页

作者： Yi, Huawei Zhang, Fuzhi Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province School of Information Science and Engineering Yanshan University Qinhuangdao China

The existing recommendation algorithms have lower robustness against shilling attacks. With this in mind, in this paper we propose a robust recommendation algorithm based on the identification of suspicious users and matrix factorization. We first give the computational methods of Deviation Degree about the Number of Ratings (DDNR) and Average Similarity of Neighbors (ASN) according to the distribution of users' ratings. Then we identify suspicious users based on the differences of computational results of users' DDNR and ASN. Finally, we introduce the matrix factorization technology which incorporates indicator function and the identification results of suspicious users to make recommendations for users. Experimental results show that the proposed algorithm not only improves the recommendation accuracy, but also has better robustness. Copyright © 2014 Binary Information Press.

关键词： Matrix algebra

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