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A study on the influence propagation model in topic attention networks

International Journal of Performability Engineering 2017年第5期13卷 721-730页

作者： Chen, Xiao Guo, Jingfeng Tian, Kelun Fan, Chaozhi Pan, Xiao College of Information Science and Engineering YanShan University Qinhuangdao066004 China Qian'An College North China University of Science and Technology Qian'an064400 China College of Economic and Management Shijiazhuang Tiedao University Shijiazhuang050043 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao066004 China

The social networks with the complex user relations and huge amount of data and hidden information, bring new opportunities and challenges for the study of information diffusion and influence maximization. In recent years, there are more and more researches on the influence maximization of topic preference. However, most of the existing researches only take the topic as an attribute of the users, and the importance of the topic in network structure is not considered. In view of this situation, firstly, this paper constructed a new topic attention network model fusing the social relation and the topic preference. Secondly, based on connected degree of set pair and Markov random walk model, we propose the calculated method of the topic preference for users, and then mining the seed set with influence by the greedy strategy. Thirdly, we propose the calculated method of the activation probability of the user based on the user relation and the topic preference, and propose the influence maximization algorithm TAN-CELF in topic attention networks. Finally, on Dou-ban network dataset, from three metrics ISST, ISRT and ISRNT, compare with algorithm L-GAUP and CELF, the experimental results show that algorithm TAN-CELF that is proposed by this paper has a higher performance on influence scope. © 2017 Totem Publisher, Inc. All rights reserved.

关键词： Data mining

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Analysis of a new type islanding detection method for micro-grid based on the calculation of variance 8

Analysis of a new type islanding detection method for micro-...

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8th IEEE International Power Electronics and Motion Control Conference, IPEMC-ECCE Asia 2016

作者： Ying, Zhang Wang, Xiaohuan Zhang, Chunjiang Feng, Jianzhou Yanshan University Key Lab of Power Electronics for Energy Conservation and Motor Drive of HeBei Province Qinhuangdao China Yanshan University Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

ISBN: (纸本)9781509012107

UL1741 rules that to realize the islanding detection, the inverter must stop running within 2s after the main grid failure occurs. However, with the increasing of the capacity of distributed generation system, in order to guarantee the stability and reliability of power supply simultaneously, IEEE Std.1547 proposed the concept that DG runs off-grid after islanding occurs. The concepts of the traditional islanding protection were attacked, the original islanding detection methods are no longer suitable for the flexible micro power grid operation system. This paper presents a new active islanding detection method which could suitable for micro-grid operation and control. The method, which under the premise of without destroying islanding operation conditions, fine-tunes the PWM modulation wave, real-time acquisition the voltage of point of common coupling, using the mathematical statistics method to extract the quadratic differential of the output voltage, according to the changes of the mathematical characteristic value in the grid connected mode and the islanding mode to judge if there was islanding occurred, and the theory basis of quantitative analysis of the disturbance quantity selection. Simulation and experiment results verify the correctness and feasibility of the proposed method. © 2016 IEEE.

关键词： Distributed power generation

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Human Movement Detection and Gait Periodicity Analysis Using Channel State Information 12

Human Movement Detection and Gait Periodicity Analysis Using...

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12th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2016

作者： Liu, Zijuan Wang, Lin Liu, Wenyuan Li, Binbin School of Information Science and Engineering Yanshan University China Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province China School of Economics and Management Yanshan University Qinhuangdao HeBei China

ISBN: (纸本)9781509056965

Under the influence of multipath effects and small scale fading, the robustness and reliability of the existing human detection methods based on radio frequency signals are easy to be impaired. In this paper, we propose a novel design that using the multi-layer filtering of channel state information (CSI) to identify moving targets in dynamic environments and analyze the gait periodicity of human. We employ an efficient CSI subcarrier feature difference to the multi-layer filtering method leveraging principal component analysis (PCA) and discrete wavelet transform (DWT) to eliminate the noises. Furthermore, we propose a profile matching mechanism for human detection and a periodicity analysis mechanism for human gait taking advantage of the above design. We evaluated it with the commodity Wi-Fi infrastructures in different environments. Experimental results indicate that our approach performs identification of human with an average accuracy of 94%. © 2016 IEEE.

关键词： Principal component analysis

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Research of Signed Networks Community Detection Based on the Tightness of Common Neighbors 6

Research of Signed Networks Community Detection Based on the...

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6th International Conference on Digital Home, ICDH 2016

作者： Xinzhuan, Hu Guo, Jingfeng Chen, Xiao Zhao, Xiaomeng School of Economics and Management Yanshan University Hebei Ave. Qinhuangdao China College of Information Science and Engineering Yanshan University Hebei Ave. Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Hebei Ave. Qinhuangdao China

ISBN: (纸本)9781509044009

According to the characteristics of positive and negative edge of signed networks, a new signed networks community detection algorithm BTCN-SNCD (Signed networks Community Detection Based on the Tightness of Common Neighbors) is proposed based on the tightness of common neighbors. Firstly, in view of the shortcomings of the traditional local similarity metrics only considering the number of common neighbors, the contribution degree and the tightness of common neighbors are defined, which can discover the initial communities with tighter structure. Secondly, for the overlapping nodes exist in initial communities, we propose overlap coefficient and community density to remerge the initial communities, thus improving community detection accuracy. Finally, the correctness and efficiency of the BTCN-SNCD algorithm are verified through a comparison with classic signed networks community detection algorithms. © 2016 IEEE.

关键词： Signal detection

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New methods of constructing quaternary sequence Pairs

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ICIC Express Letters 2016年第9期10卷 2177-2183页

作者： Jia, Yanguo Shen, Xiumin Duan, Xiaobei Song, Xiaofei School of Information Sciences and Engineering Yanshan University China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave. Qinhuangdao066004 China

In this letter, new methods of constructing quaternary sequence pairs are presented based on binary sequence pairs with two-level autocorrelation, almost perfect binary sequence pairs and cyclic shift sequences. The quaternary sequence pairs con- structed by these methods are periodic autocorrelation signals. These methods are handy and exible, and can greatly enrich the theory of quaternary sequence pairs. © 2016 ICIC International.

关键词： Autocorrelation

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Identifying important nodes in complex software network based on ripple effects

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ICIC Express Letters, Part B: Applications 2016年第2期7卷 257-264页

作者： Ren, Jiadong Wu, Hongfei Gao, Rui Huang, Guoyan Dong, Jun College of Information Science and Engineering Yanshan University China Computer Virtual Technology and System Integration Laboratory of Hebei Province No. 438 Hebei Avenue Qinhuangdao China

The structure of complex software systems can be extracted as a complex software network, and the quality of software systems largely depends on the topological structure of the software network. A small portion of important nodes plays a critical role in ensuring the stability and quality of the software system. Identifying these important nodes in software network has become an important and challenging task of software engineering. In this paper, firstly we construct a model of directed weighted software network. Then, by analyzing the bug propagation process on weighted software network, the values of some metrics related to ripple effects are calculated. Finally, important nodes whose ripple effects are larger than average ripple effect are identified by our proposed approach. Experimental results on real software data show the utility of the approach. © 2016 ICIC International.

关键词： computer software

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A new method of identifying influential nodes in complex software network based on leaderrank

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ICIC Express Letters 2016年第12期10卷 2837-2844页

作者： Huang, Guoyan Liu, Jing Chen, Xiaojuan Ren, Jiadong College of Information Science and Engineering Yanshan University China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 West Hebei Ave. Qinhuangdao066004 China

Identifying influential nodes is crucial for understanding and improving the stability and robustness of complex software network. This paper presents a new method based on LeaderRank information to identify top-k influential nodes in directed-weighted complex software network. Firstly, the function and relationship of function calling or dependency are mapped to a Directed function dependency network (DN). Secondly, a so-called stem node connected with every other node by a bidirectional link is introduced into the original network. Thirdly, an algorithm Constructing DWN (C-DWN) is used to transform a DN into a Directed-Weighted function dependency network (DWN). Finally, the Identifying Influential Node in Software Network (IIN-SN) algorithm is proposed to identify influential nodes. Experimental results show that the proposed method is effective for identifying influential nodes with the final score ranking following power-laws. The top-k most influential nodes are the same and the final score (NS) of each node is a little larger during the software evolution. What is more, we present that some factors such as in-degree of nodes and influence of connected nodes are related to the influence of nodes. © 2016 ICIC International.

关键词： Complex networks

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Research on community detection algorithm based on modularity maximum

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ICIC Express Letters 2016年第12期10卷 2995-3003页

作者： Chen, Jing Wan, Yun College of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Avenue Qinhuangdao066004 China

It is well known that the drawbacks of label propagation algorithm are high randomness, weak robustness and easy to form monster community. Many improved methods are proposed constantly in order to avoid these problems. However, the related label propagation algorithm is seldom concerned with the stability of community structure and the results of community detection. In order to obtain the high value communities, modularity and community structure are involved in detecting communities. In this paper, the algorithm CDMMCS (Community Detection based on Modularity Maximum and Community Structure) is proposed. The main idea is based on label propagation, but CDMMCS begins with some small communities, and the process of label updating is in consideration of the modularity maximum. When the label stops propagating, the communities with the same label are merged. Check the community structure of merged communities, and perform different operations according to different community structures. Experiments show that CDMMCS successfully detects communities with higher modularity values than LPA (Label Propagation Algorithm) and LPAm+ in some realworld networks. And the running time of CDMMCS is less than LPAm+. © 2016 ICIC International.

关键词： Population dynamics

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Efficient subtree results computation for XML keyword queries

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Frontiers of computer Science 2015年第2期9卷 253-264页

作者： Ziyang CHEN School of Information Science and Engineering Yanshan University Hebei 066004 China Environmental Management College of China Hebei 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Yanshan University Hebei 066004 China

In this paper, we focus on efficient construction of restricted subtree （RSubtree） results for XML keyword queries on a multicore system. We firstly show that the perfor- mance bottlenecks for existing methods lie in 1） computing the set of relevant keyword nodes （RKNs） for each subtree root node, 2） constructing the corresponding RSubtree, and 3） parallel execution. We then propose a two-step generic top-down subtree construction algorithm, which computes SLCA/ELCA nodes in the first step, and parallelly gets RKNs and generates RSubtree results in the second step, where generic means that 1） our method can be used to compute dif- ferent kinds of subtree results, 2） our method is independent of the query semantics; top-down means that our method con- structs each RSubtree by visiting nodes of the subtree con- structed based on an RKN set level-by-level from left to right, such that to avoid visiting as many useless nodes as possible. The experimental results show that our method is much more efficient than existing ones according to various metrics.

关键词： XML SLCA/ELCA RSubtree RKNs parallel

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iBole： A Hybrid Multi-Layer Architecture for Doctor Recommendation in Medical Social Networks

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Journal of computer Science & technology 2015年第5期30卷 1073-1081页

作者：宫继兵王立立孙胜涛彭思维 School of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao 066004 China

In this paper, we try to systematically study how to perform doctor recommendation in medical social net- works （MSNs）. Specifically, employing a real-world medical dataset as the source in our work, we propose iBole, a novel hybrid multi-layer architecture, to solve this problem. First, we mine doctor-patient relationships/ties via a time-constraint probability factor graph model （TPFG）. Second, we extract network features for ranking nodes. Finally, we propose RWR- Model, a doctor recommendation model via the random walk with restart method. Our real-world experiments validate the effectiveness of the proposed methods. Experimental results show that we obtain good accuracy in mining doctor-patient relationships from the network, and the doctor recommendation performance is better than that of the baseline algorithms： traditional Ranking SVM （RSVM） and the individual doctor recommendation model （IDR-Model）. The results of our RWR-Model are more reasonable and satisfactory than those of the baseline approaches.

关键词： doctor recommendation architecture random walk with restart doctor-patient tie mining time-constraintprobability factor graph model medical social network

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