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An improved community discovery algorithm in weighted social networks

ICIC Express Letters 2016年第1期10卷 35-41页

作者： Guo, Jingfeng Liu, Miaomiao Liu, Linlin Chen, Xiao College of Information Science and Engineering Yanshan University No. 438 West Hebei Ave Qinhuangdao China College of Information Science and Engineering Northeast Petroleum University No. 199 Fazhan Road Daqing China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 West Hebei Ave Qinhuangdao China

The algorithm AGMA (Automatic Graph Mining Algorithm) is improved and a novel community discovery algorithm, namely CRMA (Clustering Re-clustering Merging Algorithm) is proposed which can realize more reasonable community division for weighted social networks. Firstly, in the re-clustering stage, AGMA neglected the clustering situation of neighbors of current node and it did not take the weights of edges connecting the current node and its unclustered neighbors into account, which led to that some nodes cannot be clustered or their clustering was unreasonable. Aiming to this, the concept of the connection compactness between the node and the community is introduced, and then through clustering and re-clustering each node would be divided into the community that has the largest connection compactness with the node according to the node weight, the edge weight and the friend coecient between the node and the community. Secondly, for community division in some unweighted networks and signed networks, if there are many nodes whose clustered neighbors are less than its unclustered neighbors, the division results of AGMA tend to result in the lower modularity. In view of this problem, the concepts of positive edge weight density, the cluster density and the connection coecient between clusters are proposed. Lastly, communities are merged based on the above three concepts after re-clustering and the modularity is eectively enhanced. The higher correctness and better generality of the improved algorithm are veried through experiments. © 2016 ICIC International.

关键词： Clustering algorithms

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A DAG-based algorithm of mining frequent closed itemsets in high dimensional datasets

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International Journal of Advancements in Computing technology 2012年第19期4卷 213-222页

作者： Dong, Jun Chen, Shuai Chen, Jing Huang, Guoyan Ren, Jiadong College of Information Science and Engineering Yanshan University 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China Production Management Department Shanghai Aircraft Manufacturing Co.Ltd 200436 China

Algorithms based on row enumeration always scan and construct conditional transposed tables, which increases the execution time and space cost. To address this problem, we adopt the DAG (Directed Acyclic Graph) to compress the dataset to save the memory space. In DAG, each node is related to a rowid, and each two nodes have a corresponding directed edge which stores the common items of the two rowids. Each row is given an integer according to its coming order and the DAG follows that order. A directed acyclic graph records the relation between rows and items by doing AND(&) operation with the nodes' binary code of the edges. We also present DAGHDDM which is a new approach for mining frequent closed itemsets in high dimensional datasets. In this algorithm, we adopt the BitTable to compress the dataset firstly, and then construct DAG according to the BitTable. We increase the same items of the adjacent edges to implement pattern growth, traverse the DAG in reversal way and adopt a close-checking method to generate all frequent closed itemsets. It scans the dataset only once and does not generate candidate itemsets. The experimental results show that the proposed DAGHDDM algorithm can decrease the cost of time.

关键词： Directed graphs

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Redundant filter-based efficient Minkwoski sum computation of polyhedra

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ICIC Express Letters 2014年第10期8卷 2939-2944页

作者： Zhang, Jianfei Guo, Xijuan Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province College of Information Science and Engineering Yanshan University No. 438 West Section of Hebei Avenue Haigang District Qinhuangdao 066004 China College of Computer and Control Engineering Qiqihar University No. 42 Wenhua Street Qiqihar 161006 China

On the basis of the introduction to basic theory of Minkowski sum, we analyze the procedure of constructing the boundary of Minkowski sum and present a new method that can compute Minkowski sum of the polyhedra based on redundant information filtering. The method can filter the edges and facets that can be processed in the next computational stage, and reduce the number of the edges and facets that must be computed to improve the computing performance. The experiments show that the presented method has better performance including computing efficiency, accuracy and degeneration problems and fits for application domains that require high efficient and accurate computation. © 2014 ICIC International.

关键词： Information filtering

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A Recurrence method of attribute reduction based on rough set

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ICIC Express Letters 2013年第3 B期7卷 1025-1030页

作者： Zhang, Tao Lu, Jing Chen, Nan Gao, Zhi College of Information Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China College of Foreign Languages Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China Institute of Electrical Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China

According to the classical rough set, the attribute reduction set may be far from satisfactory due to the non-existence of core in the attribute reduction process of decision table. Aiming at this issue, this paper puts forward a recurrence method of attribute reduction;first find out the starting attributes with the highest division as the basic one, and then add the remaining attributes gradually to refine the undivided equivalence class until the non-existence of the samples which must be separated. The paper theoretically proved the relation between the traditional method and recurrence method of attribute reduction on the existence of core. The reliability of the new method was analyzed and illustrated by experiments. © 2013 ICIC International.

关键词： Decision tables

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Skin panel design for a morphing mechanism

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ICIC Express Letters, Part B: Applications 2016年第10期7卷 2161-2167页

作者： Zhao, Qiang Guo, Xliuan Xi, Fengfeng Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province College of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China Department of Aerospace Engineering Ryerson University TorontoONM5B 2K3 Canada

A segmentation method is proposed to aid rigid skin panel design for an existing modular morphing wing mechanism. The method divides the surface of the modular morphing mechanism into panels through geometry discretization, and then the skin which is made up of these rigid panels will have better rigidity and it will morph more free without any gap. The method comprises three basic morphing types based on the motion of upper platform. Wherein, the mechanism side is firstly divided into a plurality of panels and each of them is approximated to flat, and then shape changes of one panel before and after morphing are analyzed. Therefore, panels can be designed as moveable and fixed patches to achieve seamless morphing. At last, computer simulation is set up to further verify the correctness of the method. © 2016 ICIC International.

关键词： Morphing mechanism Seamless morphing Skin panel Surface segmentation

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A study on the influence propagation model in topic attention networks

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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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Outlier detection based on cluster outlier factor and mutual density

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International Journal of Intelligent Information and Database systems 2019年第1-2期12卷 91-108页

作者： Zhang, Zhongping Zhu, Mengfan Qiu, Jingyang Liu, Cong Zhang, Debin Qi, Jie School of Information Science and Engineering Yanshan University Qinghuangdao Hebei066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province 438 West Section of Hebei Street Haigang District Qinhuangdao City Hebei Province066004 China Hebei Education Examinations Authority 231 Hongqi Street Shijiazhuang City Hebei Province050000 China First Middle School of Qian An Country 347 Wutong Road Qianan Jilin131400 China

Outlier detection is an important task in data mining with numerous applications. Recent years, the study on outlier detection is very active, many algorithms were proposed including based on clustering. However, most outlier detection algorithms based on clustering often need parameters and it is very difficult to select a suitable parameter for different data set. In order to solve this problem, an outlier detection algorithm called outlier detection based on cluster outlier factor and mutual density is proposed in this paper. The mutual density and γ density is used to construct decision graph. The data points with γ density anomalously large in decision graph are treated as cluster centres. This algorithm detect the boundary of outlier cluster using cluster outlier factor called cluster outlier factor (COF), it can automatic find the parameter. This method can achieve good performance in clustering and outlier detection which be shown in the experiments. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Data mining

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AR Mechanical-Guiding Assembly system

AR Mechanical-Guiding Assembly System

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International Conference on virtual Reality and Visualization (ICVRV)

作者： Yuhan Liu Liguo Yang Yong Tang Jiangtao Li Chuanning Tang Jiangkai Jia Yanshan University The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China Yanshan University Level 16 College of Information Science and Engineering Qinhuangdao China Yanshan University Level 15 College of Information Science and Engineering Qinhuangdao China yanshan university College of Information Science and Engineering Qinhuangdao China

ISBN: (纸本)9781538684986;9781538684979

Guiding assembly system based on AR is to apply the technol-ogy of Augmented Reality to guide mechanical assembly op-eration and teach or train freshmen. By the means of adapting AR glasses(HoloLens, Magic Leap One etc.), we use virtual information to guide operating real mechanic. AR operation can achieve better effect than traditional reality training, and make industrial assembly process easier for costumers to un-derstand. It can also decrease losses caused by operational error, therefore increases efficiency safety and productivity.

关键词： Conferences virtual reality Visualization

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Rain scenes rendering algorithm combining metaball with mass-spring surface

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Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and technology Edition) 2013年第SUPPL.1期43卷 230-234页

作者： Lyu, Meng-Ya Zheng, Xuan Tang, Yong College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Qinhuangdao 066004 China

To solve the problems such as unreal effects, incomplete details in the rain scene, an algorithm to simulate water surface after rain hitting by combining Meatball with mass-spring water surface was presented. First, the raindrops model was estabished with particle system combining textures, and the water surface model was established with the mass-spring model. Secondly, the algorithm animated half globular bubbles after rain hitting with Meatball. Thirdly, water splash was simulated by means of the particle system and a gradual thinning and syncretizing technique. Finally, with the help of Cg language, the reflection and the refraction effect on the water surface, globular bubbles and water splash were simulated. The experiment shows that this approach can be used to simulate rain scenes efficiently and realistically.

关键词： Rain

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A filtering algorithm for scattered point cloud based on curvature features classification

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Journal of Information and Computational Science 2015年第2期12卷 525-532页

作者： Gu, Xiaoying Liu, Yongshan Wu, Qiong College of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao China Data Industry Research Lab Qinhuangdao China

In order to remove the noise of three-dimensional scattered point cloud, and to smooth point cloud model effectively, an algorithm which uses different filtering strategies on different feature regions of a point cloud model is proposed. The algorithm firstly estimates the normal vectors of a point cloud model by using covariance analysis method, then estimates Gaussian curvatures of the point cloud model by using parabolic fitting method, and uses the average Gaussian curvature in the k-neighborhood as the threshold, to divide the point cloud model into flat neighborhood type regions and mutant neighborhood type regions, and, we use improved median filtering algorithm and bilateral filtering algorithm on different feature regions, so as to achieve the purpose of smoothing scattered point cloud. Experimental results show that it has a very good smoothing effect and maintains the detail features of the point cloud model, which has proved the algorithm is simple and effective. Copyright © 2015 Binary Information Press.

关键词： Three dimensional computer graphics

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