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A weighted clustering algorithm based on user’ access sequence similarity

ICIC Express Letters 2016年第10期10卷 2363-2370页

作者： Li, Weina Han, Gaowei Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave. Qinhuangdao066004 China

Consider traditional clustering algorithms seldom had a research on users’ visit behavior and content, and they cannot cluster users with similar visit behavior into a community easily. Behavior of user cannot cluster users with similar visit behavior i also reflect usery. Behavior Therefore, setting about the log of user’s access behavior, in view of visitor volume, sequences of accessing keywords and time interval between keywords, a weighted clustering algorithm based on sequence similarity which is called K-Similar is put forward. Starting from behavior of user’s access to document, users are clustered, and important users are divided into a community. Then, literature needs of users in the same cluster are mined. This algorithm has been verified in users users are log data in CNKI, available for academic publishing. Experimental results show that K-Similar is more efficient in efficiency and accuracy. It can obtain more interesting user communities and show academic publishing demand of special users. © 2016 ICIC International.

关键词： Clustering algorithms

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New construction of quaternary sequence with even period based on cyclotomic classes of order two

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ICIC Express Letters 2015年第7期9卷 1959-1964页

作者： Jia, Yanguo Shi, Yan Duan, Xiaobei Shen, Xiumin School of Information Science and Engineering Yanshan University No. 438 West Hebei Street Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Heibei Province No. 438 West Hebei Street Qinhuangdao China

In this paper, we present a new method for constructing quaternary sequence with even period 2f based on cyclotomic classes of order two. Under the premise of v = 2f +1, we construct two binary sequences with period 2f. Then we can construct a new quaternary sequence from those two binary sequences by using the reverse Gray Mapping. The distribution of autocorrelation function of the proposed quaternary sequence is also derived, which is decided by the parity of f. © 2015, ISSN 1881-803X.

关键词： Binary sequences

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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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In-rank: An entropy-based informative nodes mining method in complex software network

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ICIC Express Letters 2016年第7期10卷 1683-1689页

作者： Ren, Jiadong Li, Yanling Wu, Hongfei Liu, Yang Zhang, Peng College of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Avenue Qinhuangdao066004 China

It is a fundamental issue to find a small subset of influential individuals in a complex network such that they can spread information to the largest scope of nodes in the network. Informative functions in complex software network can lead maximum information propagation scope, and mining such function nodes is important to understand the system’s topology structure and information transfer flows. In this paper, a novel topk informative nodes mining approach based on global information in directed-weighted complex software network is proposed. Firstly, we map functions and call relationships between them as a Directed-Weighted Function Call Network (DWFCN). Secondly, an algorithm path-compute based on Software Executing Path Sequence (SEPS) generated by Depth-First-Search strategy is used to compute the software executing paths and get nodes’ information Accessible Set (AS). Thirdly, algorithm Entropy-Compute is proposed to calculate each source node’s information entropy in each information transfer flow process. Finally, an Informative Node Rank (IN-Rank) algorithm is put forward to mine most informative nodes. Experimental results show that our new method is accurate and effective. © 2016, ICIC Express Letters Office. All rights reserved.

关键词： Mining

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Improving Vision Transformers with Nested Multi-head Attentions

Improving Vision Transformers with Nested Multi-head Attenti...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jiquan Peng Chaozhuo Li Yi Zhao Yuting Lin Xiaohan Fang Jibing Gong School of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Microsoft Research Asia Beijing China

Vision transformers have significantly advanced the field of computer vision in recent years. The cornerstone of these transformers is the multi-head attention mechanism, which models interactions between visual elements within a feature map. However, the vanilla multi-head attention paradigm independently learns parameters for each head, which ignores crucial interactions across different attention heads and may result in redundancy and under-utilization of the model’s capacity. To enhance model expressiveness, we propose a novel nested attention mechanism, Ne-Att, that explicitly models cross-head interactions via a hierarchical variational distribution. We conducted extensive experiments on image classification, and the results demonstrate the superiority of Ne-Att.

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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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A PTV method based on SIFT feature points matching for velocimetry measurement of oil-water two-phase flow in horizontal pipelines

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第12期8卷 195-206页

作者： Kong, Weihang Li, Lei Kong, Lingfu Li, Yingwei Xie, Na School of Information Science and Engineering Yanshan University QinhuangdaoHebei China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Hebei China Information Department of Library Yanshan University QinhuangdaoHebei China

Due to the advantages of scale invariant feature transform (SIFT) feature points on the invariant to image scale, brightness, rotation, occlusion, noise and so on, this paper proposes a Particle Tracking Velocimetry (PTV) method, based on SIFT feature points matching for velocity measurement of oil-water two-phase flow in horizontal pipelines. The oil-water two-phase flow with large droplet diameter, oil droplets overlap, ununiform lighting, and the centroid position of oil droplets can’t be obtained only by using traditional PTV methods through morphological processing. However, in this paper, the algorithm can directly achieve the average velocity of the flow field according to the positions of correctly matched SIFT feature points, and there is no need to extract the centroid coordinates of each oil droplet. The experimental results show that the proposed algorithm not only can be used in the average velocity measurement of oil-water two- phase flow in horizontal pipelines, but also can reach 95% in the measuring accuracy when the matching feature points are enough sufficient. © 2015 SERSC.

关键词： Velocity measurement

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

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Journal of Convergence Information technology 2012年第21期7卷 467-476页

作者： Huang, Guoyan Chen, Shuai Ren, Shenyuan Dong, Jun College of Information Science and Engineering Yanshan University Qinhuangdao Hebei 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China College of Computer Science Sichuan University Chengdu Sichuan 610000 China

In order to fully utilize the minimum support threshold to prune the rowset search space and avoid scanning the whole dataset in close-checking, we proposed two new data structure, Rowset-Itemset-Hybrid-Search-Tree (RIHS-Tree) and Frequent-Closed-Itemset-Rowset-Tree (FCIR-Tree). The former stores the rowsets which share common rowid prefixes, according to some predefined order of rowids. Each path from the root node to the leaf node represents a rowset in which the rowids increase. The later also stores the large rowsets which also share common rowid prefixes. The corresponding closed itemsets are stored in the nodes carrying the last rowids in rowsets. Moreover, a new algorithm, RIHS-Tree-based algorithm for mining frequent closed patterns (FCIM-RIHS), is proposed. We translate the whole dataset into a transposed table, construct RIHS-Tree according to the rowsets in the transposed table and use a bottom-up search strategy to traverse RIHS-Tree. In the process of mining, we use the rowsets-inclusion strategy to implement pattern growth and then obtain large rowsets with their corresponding frequent closed itemsets. In FCIR-Tree, if the nodes in the subtree rooted by the nodes carrying the last rowid in the rowsets do not contain the found itemsets, the found itemsets are frequent closed itemsets. The experiment results with dataset demonstrate that FCIM-RIHS has highly efficiency.

关键词： Trees (mathematics)

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A novel approach to identify influential functions in complex software network based on complex network

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ICIC Express Letters 2016年第2期10卷 485-492页

作者： Huang, Guoyan Chen, Xiaojuan Wu, Hongfei Zhang, Peng Ren, Jiadong College of Information Science and Engineering No. 438 West Hebei Ave Qinhuangdao China Computer Virtual Technology and System Integration Laboratory of Hebei Province Yanshan University No. 438 West Hebei Ave Qinhuangdao China

Identifying influential nodes is an important issue in understanding the process of information diffusion in complex software networks. Researchers generally define functions as nodes, and relationship of function calls as edges to map software into complex network. This paper proposes a novel approach to identify the influential nodes in complex software network based on complex network. Firstly, we map the function and relationship of function calling or dependency to a directed weighted call network (DWCN). Secondly, we define NodeScore (NS) to evaluate the importance of nodes in network. It has higher influence when the node has lager value of NS. The NS of each node is calculated by two parts in our opinion, Direct Dependency Nodes (DDN) and Indirect Dependency Nodes (IDN). Thirdly, algorithm ComputeNodeScore is proposed to calculate NS of each node. Finally, we mine top-k nodes based on the NS. Experimental results of various versions about software Tar and cflow show the approach is effective for identifying the influential nodes. © 2016, ICIC Express Letters ICIC International.

关键词： Complex networks

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Angle historgam model of directional relationship in 3D based on Double-projection and Rounded-subdivision

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Journal of Information and Computational Science 2014年第18期11卷 6471-6478页

作者： Kong, Dehan Liu, Yongshan Ma, Junlei Department 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

The formal model of spatial directional relations is one of the most important parts in spatial relation research. The most of models are based on Minimum Bounding Rectangle (MBR), and they are not compliant with the regular pattern of human cognition. In order to get a closer conclusion to human cognition on directional relationship, Angle Histogram model based on Double-projection and Rounded-subdivision (AHDPRS) is proposed in this paper. The model uses the maximum inscribed circles to find out the maximum parts of the object, and calculates the directional relationship between the centers of the circles. This model ignores the inessential details to ensure the result which will be closer to human cognition. The experiments show that this model is feasible.

关键词： Graphic methods

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