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A high dimensional data clustering algorithm based on hypergraph

Journal of Computational Information systems 2012年第23期8卷 9839-9846页

作者： Liu, Yongshan Chen, Wei Shang, Xuehui Lv, Yongteng Han, Yuanyuan Liu, Chang 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

High dimensional data clustering is an important issue for data mining. Firstly, the records in the dataset are mapped to the vertices of hypergraph, the hyperedges of hypergraph are composed of the vertices which have the same value on one certain attributes. Then a multilevel hypergraph partitioning algorithm is used to find k parts of the hypergraph. Finally, the clusters with good quality are choosed out by computing the value of clusters validity. The experimental results show that the new algorithm can efficiently construct high quality clusters. ©2012 by Binary Information Press.

关键词： Data mining

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Subspace clustering over high-dimensional data stream based on grid density and attribute relativity

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Advances in Information Sciences and Service Sciences 2012年第17期4卷 91-99页

作者： Huang, Guoyan Miao, Liyun Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao City 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

The traditional clustering algorithms often fail to detect meaningful clusters in high-dimensional data space. To improve the above shortcoming, we propose GDRH-Stream, a clustering method based on the attribute relativity and grid density for high-dimensional data stream, which consists of an online component and an offline component. First, the algorithm filters out redundant attributes by computing the relative entropy. Then we define a weighted attribute relativity measure and estimate the relativity of the non-redundant attributes, and form the attribute triple. At last, the best interesting subspaces are searched by the attribute triple. On the online component, GDRH-Stream maps each data object into a grid and updates the characteristic vector of the grid. On the offline component, when a clustering request arrives, the best interesting subspaces will be generated by attribute relativity. Then the original grid structure is projected to the subspace and a new grid structure is formed. The clustering will be performed on the new grid structure by adopting an approach based on the density grid. Experimental results show that GDRH-Stream algorithm has better quality and scalability.

关键词： Relativity

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An algorithm based on bit complementary tree for mining closed frequent itemsets

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International Journal of Advancements in Computing technology 2012年第22期4卷 427-435页

作者： Ren, Jiadong Yang, Xuan Dong, Jun College of Information Science and Engineering Yanshan University Qinhuangdao City066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

In recent years, closed frequent itemsets mining has become a hot topic. In this paper, we present an algorithm BCTCF, which is based on Bit complementary tree (BCTree) in order to mine closed frequent itemsets efficiently. First we adopt bit vectors to compress the database and define a novel structure, BCTree, in which a node stores two bit vectors that are complementary and each path is given a prime value. Based on the left-most bit in the bit vectors we adopt a divide-and-conquer strategy which handles the itemsets separately and then according to the prime unique feature we can get the closed frequent itemsets quickly and it makes us need not to mine all the frequent itemsets first. Both the divide-and-conquer strategy and prime unique can decrease the runtime. Experiment results show that BCTCF is very effective and scalable.

关键词： Forestry

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An algorithm based on temporary table for mining top-k closed frequent patterns in data streams

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2012年第20期6卷 582-589页

作者： Wang, Peilong Yang, Xuan Zhang, Yuanyuan Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao City 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

In this paper, we present an algorithm TKBT(top-k closed frequent mining based on TKTT) to mine top-k closed frequent itemsets in data streams efficiently. First according to the consecutive and changeable characteristics of the data from data streams in sliding window, a novel structure, BWT(bit-vector window table) is defined. In BWT horizontal direction we use bit vectors to express the transactions, record the count of items in the oldest, the newest window and all the windows a t current time, which decreases the calculating time of the items count when a new window slides in. In BWT vertical direction we set window partition, which makes us just need replace the oldest window information with the corresponding newest window when a new window comes. The construction of TKTT (top-k temporary table) is based on BWT. The itemsets in TKTT are ranked in a descending count order. TKBT can get top-k closed frequent itemsets by connecting the candidates in TKTT using top-down strategy. The candidate number is reduced by using closed itemset displace its subset and less connection times are contributed to the less runtime. Experiment results show that TKBT is very effective and scalable.

关键词： Closed frequent item sets Data streams Sliding window Top-K

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A clustering algorithm for heterogeneous objects based on information dissimilarity

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Journal of Convergence Information technology 2012年第22期7卷 93-100页

作者： Chen, Ziyang Wang, Xuefeng Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao City 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao City 066004 China

Due to the introduction of weight of attributes, most of existing dissimilarity measures can not accurately reflect the difference between two heterogeneous objects, and then clustering quality was decreased. In this paper, we present HIDK-means, an approach for clustering heterogeneous data based on information dissimilarity. At first, the algorithm defines heterogeneous information dissimilarity between two heterogeneous objects based on Kolmogorov information theory, and calculates approximately heterogeneous information dissimilarity by a universal probability of an object. Then, in the clustering process, the algorithm selects the initial cluster centers by maximum sum of dissimilarity. After that, each remaining object is assigned to a cluster center which has the smallest dissimilarity with it and the criterion function is calculated. Iteratively, cluster centers are updated and the process is ceased until the criterion function converges or the iteration number reaches the pre-set threshold. The experimental results show that the proposed algorithm HIDK-means is effective in clustering heterogeneous objects and also scalable to large datasets.

关键词： Clustering algorithms

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A clustering algorithm for data stream based on spatial directed graph with core

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Journal of Convergence Information technology 2012年第19期7卷 131-139页

作者： Dong, Jun Yuan, Xuemei Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao City 066004 China Key Laboratory for Computer Virtual Technology System Integration of Hebei Province Qinhuangdao City 066004 China

Due to the randomness of the partition of grids, the edge points of clusters might be partitioned into the sparse grids. These points would become noise information out of clusters when we cluster data stream by grid-density based algorithm. A data stream clustering algorithm based on spatial directed graph with core, SDGCStream, is proposed. It uses the spatial directed graph and the orthocenter of the sparse grids to handle the edge points of clusters. At first, the algorithm defines a structure SDGC (Spatial Directed Graph with Core) to store the summary statistics of data stream. The vertices of SDGC are maintained as the stream arriving. When the clustering quest comes, the edge information is generated. The initial clustering results are got through clustering on SDGC, then we judge whether the points of sparse grids which are adjacent to the border of a cluster belong to the cluster according to the orthocenter information and the border vertices of SDGC. At last, a strategy based on the distance between clusters is presented to adjust the clustering results after handling the border of clusters. The experimental results on synthetic and real datasets show the better validity of SDGCStream on handling the edge data points of clusters, and the scalability as the increasing of the length and dimensions of data stream.

关键词： Clustering algorithms

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The effects of DHPG stimulation on spikes and theta frequency oscillations and spike-theta oscillation relations in rat MSDB slice

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Journal of Convergence Information technology 2012年第17期7卷 442-449页

作者： Wen, Dong Ouyang, Gaoxiang Peng, Ce Li, Xiaoli Lu, Chengbiao Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Yanshan University Qinhuangdao Hebei China Institue of Electrical Engineering Yanshan University Qinhuangdao Hebei China National Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing 100088 China

Neuronal oscillations in the theta frequency range and spikes have been reported in many cortical areas in the information processing, but the role of spikes play in cortical processing remains unclear. The aim of this study was to examine the role of DHPG in the generation of oscillatory field activity at theta frequency in the medical septal diagonal band of Broca (MSDB) slice prepared from rat brain, and to determine the phase relationship between spikes and theta oscillations. The DHPG induced large amplitude field population spiking activity, which is correlated linearly with the field theta oscillations. The relationship between timing of spikes and the phase of theta oscillation was determined by an analysis of circular statistics. Further analysis with Rayleigh test revealed that the relationship of phase-locking between spikes and theta rhythm is of statistical significance. These data demonstrate that DHPG-sensitive neuronal networks within medial septum are able to generate theta oscillations which are modulated by large amplitude population spikes and phase-locking of spikes to the theta rhythm suggest the role of memory enhancement in the presence of mGluR1 activation.

关键词： Rats

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The study to eeg synchronization in alzheimer's disease based on new s estimator method

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Journal of Convergence Information technology 2012年第22期7卷 1-7页

作者： Wen, Dong Chen, Ruihong Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Yanshan University Qinhuangdao Hebei 066004 China Division of General Internal Medicine Xiantao First People's Hospital Xiantao Hubei 433000 China

Synchronization decay of resting state EEG has shown that cognitive dysfunction in Alzheimer's disease (AD) was relevant to a loss of functional connectivity in intermediate frequency bands. The new S estimator (NSE) proposed recently by us quantifies synchronization between neuronal signals at multiple *** paper meant to explore the behavior of synchronization of multichannel EEG in AD and healthy normal controls at rest, and preliminarily make clear the clinical significance of the NSE in AD *** (EEG) were recorded from 10 AD patients and 12 age-matched healthy normal controls (NC). NSE values were computed both across the all frequency band and separately in the delta, theta, alpha, beta (including beta1, beta2 and beta3), and gamma bands. The Mini-Mental Status Examination (MMSE) was used to assess the symptom severity of AD patients and *** values in the beta1 and beta2 bands were significantly lower in AD patients than in NC. NSE values in the alpha and beta1 bands were positively correlated with the MMSE scores in all participants (AD and NC). In AD patients, NSE values in the alpha, beta1 and beta2 bands were also positively correlated with MMSE *** results suggest that NSE values are a useful correlate of EEG synchronization in AD patients.

关键词： Synchronization

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Fourth Normal Form and Free Redundancy for XML Document Based on Path Expression

Fourth Normal Form and Free Redundancy for XML Document Base...

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International Conference on computer Science and Network technology

作者： Zhongping Zhang Zhixiao Liu College of Information Science and Engineering The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University College of Information Science and Engineering Yanshan University

ISBN: (纸本)9781467329637

With eXtensible Markup Language (XML) becoming more and more popular, to avoid the redundancy, XML schema design has become an important issue. So the normalization of XML is a hotspot in research field. Similar to relational database, this paper is database based with the goal of eliminating the data redundancy, to study the concepts of path expression in Document Type Definition (DTD). In this paper, XML is extended with functional dependency (XFD) and multi-valued dependency (XMVD), which are fundamental to semantic specification. And make formalized definitions on XFD and XMVD;Based on the concepts of XML tree and data dependency, it provides the description of key and redundancy. On the condition of the coexistence of XFD and XMVD, it further proposes the terms to meet the fourth normal form (4XNF) and provides theorem to determine the XML document tree which meets the above terms without redundancy, and the sound of the 4XNF is proved by experiment.

关键词： Normalization Functional dependency Multi-valued dependency key Redundancy The fourth normal form redundancy XML document extensible markup language normalization data redundancy data dependency

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An identity authentication algorithm in the object name service of the internet of things for heat meter

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Advances in Information Sciences and Service Sciences 2012年第22期4卷 174-181页

作者： Han, Yuanyuan Liu, Yongshan Chen, Wei Liu, Chang Shang, Xuehui Lv, Yongteng The Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Yanshan University Qinhuangdao City 066004 China College of Information Science and Engineering Yanshan University Qinhuangdao City 066004 China

In the environment of the Internet of Things for heat meter, insecurity of the object name service (ONS) is likely to lead to the leakage of user privacy. In order to solve this problem, an identity authentication algorithm is proposed. First, the certificate authority may generate parameters of elliptic curve and its own public key and private key, and announce the parameters and its own public key, so that the registered users can inquire and use them. Second, the client registers at the certificate authority. The certificate authority will generate the public key of the client and the evidence of the client's private key which is signed by private key of the certificate authority. If the generated evidence of private key passes verification of the client, the client will generate its own private key. When a client sends a query request to an ONS server, the ONS server will authenticate identity of the client. If the client gets through the authentication, the ONS server will respond to the query request. The experimental result shows that this algorithm has high security and can avoid the ONS server providing query service for illegitimate client, so as to ensure the security of user privacy.

关键词： Internet of things

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