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Journal of Computational Information Systems 2015年第2期11卷 535-545页

作者： Ren, Jiadong Li, Weina Han, Gaowei College of Information Science and Engineering Yanshan University Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

Dissimilar path detection is an important task in software behavior detection. Previous dissimilar path mining algorithms ignore time-interval weight and dissimilarity. Therefore, a dissimilar path detecting algorithm called Graph-Dissimilar-Detect in complex software behavior network based on time-interval weight and dissimilarity is put forward. Firstly, weighted complex software behavior network model is built. DFS is adopted for the network to obtain paths. Secondly, Path-Length-Constraint is designed to prune some useless paths. Time-interval-Constraint is devised to prune some weak relation between software behaviors. Strong-Path-Checking is developed to prune weighted key sub-paths. Thirdly, KPath-Mine is designed to mine weighted key paths. Fourthly, definitions of dissimilar paths and path dissimilarity are provided and Dissimilar-Path-Mine is devised to find dissimilar paths. Experimental results show Graph-Dissimilar-Detect algorithm has a good scalability in detecting dissimilar paths in complex software behavior network. Furthermore, considering time-interval and path dissimilarity, more interesting and accurate key paths and dissimilar paths can be found. 1553-9105/Copyright © 2015 Binary Information Press

关键词： Graph theory

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Road network information based edge bundling

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Journal of Information and Computational Science 2015年第13期12卷 4909-4918页

作者： Nie, Junlan Zhang, Jikai Xin, Shuyue Guo, Dongliang 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

To solve edge confusion problems in the geo-related graph visualization, here we present an edge bundling algorithm based on the road network information. First, the improved Dijkstra shortest path algorithm is employed to calculate the related path of original edges, and slicing quadratic Bezier curves are fitted out to replace original edges according to these path information. And then, the curve segments that satisfy conditions are merged together according to the control point consolidation strategy and thickened according to their weights, which simplifies the bundling result and also effectively shows the heat of each path;Finally, for the interested curves in the human-computer interaction, highlighted transition colors are introduced to character their directivity, and the effect is intuitive. The experimental results show that, our algorithm can effectively bundle original edges, which reduces the confusion degree of the graph. Meanwhile, the bundling result is more close to the original path, which improves the readability and understandability of the graph effectively. ©, 2015, Journal of Information and Computational Science. All right reserved.

关键词： Human computer interaction

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Community detection algorithm in signed social networks based on statistics and merger

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Journal of Information and Computational Science 2015年第15期12卷 5589-5599页

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

Researches on community detection in signed social networks focus on the assignment of positive and negative edges. However, the community detection approaches that positive and negative edges are handled separately in two phases cannot make full use of negative edges, which seriously affects the accuracy of community detection. To solve the problem, a new algorithm called CDA SM (Community Detection Algorithm Based on Statistics and Merger) is proposed: merge into the two phases as an unified process;in the process of community detection, the node shall be added to the community in which the node has the maximum contribution as well as the minimum interference degree. The accuracy and time efficiency of CDA SM have been demonstrated through a set of experiments including both un-weighted common networks and un-weighted signed social networks. © 2015 by Binary Information Press

关键词： Signal detection

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Analysis on impact of node failure in software execution network

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Journal of Computational Information Systems 2015年第6期11卷 2217-2225页

作者： He, Haitao Ren, Rong Zhang, Bing Ren, Jiadong 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

One or few failure nodes will cause cascading failure in software network, which would bring about security issues. Thus, analyzing nodes becomes an indispensable aid in software security. In this paper, software execution process is abstracted as weighted complex network. Based on this, a cascading failure diffusion analyzing (CFDA) algorithm is put forward to evaluate the impact of node failure on software during its runtime dynamically. It explores nodes' failure spreading range and the number of infected nodes by malicious attacks on high in-strength nodes and strong failure propagation probability nodes in software execution networks respectively. Meanwhile, the propagation behavior of cascading failures in the software system is studied. The experiment results prove that strong failure propagation ability nodes under attack have greater devastating impact on software than others. Copyright © 2015 Binary Information Press.

关键词： Complex networks

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Non-human-like characters' facial animation driven by one or two actors

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Journal of Information and Computational Science 2015年第10期12卷 3937-3944页

作者： Tang, Yong Liu, Yuhan Guo, Dan Liang, Haiyan Luo, Yanqing Lv, Mengya College of Information Science and Engineering Yanshan University Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

We present a novel system that can transfer facial expressions from an actor to a non-human-like character. Compared with a lot of previous studies, our system requires no special light conditions or facial markers for actors' performance. More significantly, our work can find vertex correspondences between the human face and characters with dissimilar facial structures by creating local-coordinate systems on the character. Experiments show that in our system not only one actor's performance is accurately transferred to non-human-like characters but also two actors' expressions can be simultaneously retargeted to one non-human-like character. Through our approach, virtual characters can have much more vivid expressions. 1548-7741/Copyright © 2015 Binary Information Press

关键词： Animation

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Improving neighbourhood quality for CHUCKY: An empirical study

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Journal of Computational Information Systems 2015年第16期11卷 5967-5977页

作者： Zhao, Fengda Yang, Ke Ren, Jiadong 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

Vulnerability discovery is at the centre of attention in computer security. Most vulnerability detection methods need considerable human auditing, thus making vulnerability detection inefficient and unreliable. Similar neighbourhood-based missing check detection method solves this problem to some degree. However, semantic noises that degrade the quality of the neighbourhood list remain. To reduce these noises, we firstly define a q-gram-based name similarity to measure the correlation of function names or file names. The context similarity of function is then defined to measure the commonness of two functional working environment. Finally, two filters are proposed: one is the naive neighbourhood filter which filters irrelative functions by name similarity;the other is the improved integrate neighbourhood filter, which awards strong correlated functions by recognising remarkable name and context similarity. The filter-based methods are experimentally evaluated in five widely used open-source software and are compared with the original method. Result shows that the improved neighbourhood rank lists are more accurate than the original list. © 2015 by Binary Information Press

关键词： Static analysis

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Grid resource dynamic replication strategy based on access frequency and time cost

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Journal of Computational Information Systems 2015年第6期11卷 1973-1982页

作者： Zhang, Zhongping He, Long The School of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

Data grid provides a large amount of computing resources and storage space to handle data-intensive applications. Because of the limitation of available resources and the production of large-scale workload in grid, the effective use of grid resources has become a major challenge. Data replication can reduce the bandwidth consumption, improve the fault-tolerant ability and enhance the extensibility. A grid resources dynamic replication strategy based on the access frequency and time cost is given in this paper. The proposed strategy deletes the file by considering two important parameters: access frequency and transmission costs. In the replica selection strategy, the best replica is selected by considering the waiting time of the replica request queue in the storage and the data transfer time. The simulated results with OptorSim show that the proposed replication strategy gives better performance compared with DHRA algorithm. Copyright © 2015 Binary Information Press.

关键词： Data transfer

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Method of periodic dynamic pattern mining based on complex network

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Journal of Computational Information Systems 2015年第21期11卷 7849-7856页

作者： Wang, Lei Jiang, Liya Dong, Jun Huang, Guoyan Ren, Jiadong 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 Hebei Normal University of Science and Technology Qinhuangdao China

Traditionally, analysis of dynamic network has been focused only on a single snapshot or integrated network obtained over a period of time. However, the temporal feature in dynamic network has been ignored. In this paper, periodic dynamic pattern (PDP) mining method is proposed to discover the dynamic evolution rule of social networks. We define a periodic dynamic pattern based on complex network, and construct matrix of graph (MG) to present the evolution of complex network over time. Moreover, a regular edge pattern searching (REPS) algorithm based on MG is designed. It is used to select frequent and regular edge existence sequence (EES) in MG with progressive scan. To improve efficiency of the algorithm, sequences according with frequency threshold and REP should be transformed to decimal integer. Then, depth-first search method is used to mine PDP, which owns the same REP in dynamic network. So, we can predict future network evolution and control its behavior. Experimental results demonstrate that our method is an effective periodic dynamic pattern mining. Copyright © 2015 Binary Information Press.

关键词： Complex networks

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Frequent jump pattern mining based on complex network

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Journal of Computational Information Systems 2015年第17期11卷 6451-6458页

Many researchers are devoted to find frequent pattern in static network. Due to these frequent patterns are usually defined as frequent existence patterns which satisfy given support threshold in network. However, the temporal feature in dynamic network is ignored. In this paper, frequent jump pattern (FJP) is proposed, it not only represents frequent pattern but also can show regular behavior in evolving social network. Furthermore, jump patterns are robust against noise in the analysis of dynamical process. We construct matrix of directed graph (MDG) to present the evolution of complex directed network over time. Moreover, a frequent jump pattern searching algorithm (FJPSA) based on MDG is proposed to find dynamic evolution rule of social network. FJP mining is a technique which can be used in many application fields, such as explaining biological evolution and mining customer behavior regularity in social network. Experimental results demonstrate that our method could effectively mining FJP-graph. © 2015, by Binary Information Press

关键词： Directed graphs

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An improved algorithm for community discovery in weighted social networks

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Journal of Information and Computational Science 2015年第18期12卷 6873-6881页

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

The problems of AGMA (Automatic Graph Mining Algorithm) are improved and a novel algorithm, namely CRMA (Clustering Re-clustering Merging Algorithm) is proposed which can realize more reasonable community division for weighted social networks. Firstly, when re-clustering nodes, AGMA neglected the clustering situation of its neighbors and didn't take into account the weight of the edge connecting the current node and its unclustered neighbor, which led to unreasonable clustering. Aiming to this, the concept of the connection compactness is introduced. Then according to the node weight, the edge weight and the friend coefficient, each node would be clustered into the community has the largest connection compactness with itself. Secondly, for community division in some unweighted networks and signed networks, if there are many nodes whose clustered neighbors is less than its unclustered neighbors, the division results of AGMA tend to produce many small communities, which would result in the lower modularity. In view of this problem, the concepts of positive edge weight density, the cluster density and the connection coefficient between clusters are proposed. Lastly, we merge communities based on the above three concepts and the modularity is effectively enhanced finally. The higher correctness and better generality of the improved algorithm are verified through experiments. © 2015 by Binary Information Press.

关键词： Clustering algorithms

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