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D-LDA: A topic modeling approach without constraint generation for semi-defined classification

D-LDA: A topic modeling approach without constraint generati...

引用

10th IEEE International Conference on Data Mining, ICDM 2010

作者： Zhuang, Fuzhen Luo, Ping Shen, Zhiyong He, Qing Xiong, Yuhong Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS China Graduate University of Chinese Academy of Sciences China Hewlett Packard Labs China Innovation Works China

ISBN: (纸本)9780769542560

We study what we call semi-defined classification, which deals with the categorization tasks where the taxonomy of the data is not well defined in advance. It is motivated by the real-world applications, where the unlabeled data may also come from some other unknown classes besides the known classes for the labeled data. Given the unlabeled data, our goal is to not only identify the instances belonging to the known classes, but also cluster the remaining data into other meaningful groups. It differs from traditional semi-supervised clustering in the sense that in semi-supervised clustering the supervision knowledge is too far from being representative of a target classification, while in semi-defined classification the labeled data may be enough to supervise the learning on the known classes. In this paper we propose the model of Double-latent-layered LDA (D-LDA for short) for this problem. Compared with LDA with only one latent variable y for word topics, D-LDA contains another latent variable z for (known and unknown) document classes. With this double latent layers consisting of y and z and the dependency between them, D-LDA directly injects the class labels into z to supervise the exploiting of word topics in y. Thus, the semi-supervised learning in D-LDA does not need the generation of pairwise constraints, which is required in most of the previous semi-supervised clustering approaches. We present the experimental results on ten different data sets for semi-defined classification. Our results are either comparable to (on one data sets), or significantly better (on the other nine data set) than the six compared methods, including the state-of-the-art semi-supervised clustering methods. © 2010 IEEE.

关键词： Classification (of information)

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Unstructured P2P-enabled service discovery in the cloud environment

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作者： Zhou, Jing Shi, Zhongzhi Communication University of China Beijing 100025 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)3642163262

As the Cloud computing appears to be part of the mainstream computing in a few years, the number of the services it provides, its users, and the requests of these services will be on the rise accordingly. To deliver satisfactory experience to Cloud users, it is essential that highly scalable techniques for service discovery should be available. We embarked on a preliminary study, in Cloud environments, on service discovery by adopting an unstructured P2P technique. In the context of Cloud computing, we start by examining proposed and deployed solutions to service discovery, discuss the methodology of developping efficient mechanisms for service description, description indexing, and query routing, and finally identify open issues. © 2010 IFIP.

关键词： Cloud computing

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A Secure Distributed key Management Scheme for AD Hoc Network

A Secure Distributed Key Management Scheme for AD Hoc Networ...

引用

2010 IEEE International Conference on Information Theory and Information Security(2010 IEEE 国际信息论与信息安全会议)

作者： Xianping Yuan Yan Xu Hong Zhong Jia Yu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Univers College of Information Engineering Qingdao University Qingdao China

An identity-based threshold key management scheme without secure channel is proposed for ad hoc network. The master private key, which is shared among all nodes by the Shamir's secret sharing scheme, is produced by all nodes when network is formed. The nodes’ public keys are derived from their identities. In order to get the private key, each node needs to prove their identity to distributed CAs using a zeroknowledge proof protocol to get the share of private key. Compared with former schemes, our scheme doesn’t need any local registration authority(LRA), which is easy to be compromised by adversary. When a node leaves the network, shares of the master private key would be renewed. In the end, we prove our scheme is correct and secure.

关键词： Ad hoc networks Public key Polynomials Protocols Wireless communication

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GPU-Based Accelerated FDTD Simulations for Double Negative (DNG) Materials Applications

GPU-Based Accelerated FDTD Simulations for Double Negative (...

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2010 International Conference on Microwave and Millimeter Wave Technology(2010国际微波与毫米波技术会议 ICMMT2010)

作者： Shen Chen Sun Dong Wu Xian-liang Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei 230039 china

Recently, double-negative meta-materials are widely studied in scientific research. The double-negative (DNG) mediums are characterized by simultaneous negative permittivity and permeability. In order to make the FDTD method analyze the electromagnetic scattering and propagation for double-negative (DNG) medium, z-transform is applied to the FDTD method in the double-negative (DNG) medium. For the simulations, extremely large computer memory space and a long computational time b required. A parallel algorithm for the FDTD method on the state of the art graphics hardware is presented. The parallel computing techniques can be used to reduce the computation time significantly and have been widely applied in various complex FDTD applications. In this paper, we simulate the interaction between electromagnetic wave and DNG medium, and describe an impact of new GPU features on development process of an efficient Finite Difference Time Domain (FDTD) implementation.

关键词： Acceleration Finite difference methods Time domain analysis Electromagnetic scattering Computational modeling Permittivity Permeability Electromagnetic analysis Electromagnetic propagation Computer simulation

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Research of neural network algorithm based on FA and RBF

Research of neural network algorithm based on FA and RBF

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2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010

作者： Ding, Shifei Jia, Weikuan Su, Chunyang Chen, Jinrong School of Computer Science and Technology China University of Mining and Technology Xuzhou 221008 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China

ISBN: (纸本)9781424463503

This paper proposes a radial basis function (RBF) neural network algorithm based on factor analysis (FA-RBF) with the architecture feature of RBF network when the data are high-dimensional and complex. By reducing the feature dimension of the original data, FA-RBF algorithm regards the data after dimension reduction as the inputs of the RBF network, and then trains and simulates the network. The algorithm obviously simplifies the network architecture. By analyzing an example, the results show when the algorithm's predicted precision is not reduced, the convergence velocity is improved, the running time is saved and the error of the predicted value is reduced. In order to test and verify the validity of the new algorithm, we compare it with the RBF neural network algorithm based on principal component analysis (PCA-RBF), the predicted results of FA-RBF algorithm are better than the results of RBF and PCA-RBF algorithm. © 2010 IEEE.

关键词： Radial basis function networks

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Image denoising based on non-local means and multi-scale dyadic wavelet transform

Image denoising based on non-local means and multi-scale dya...

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2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010

作者： Yu, Gang Yin, Yong Wang, Hongjun Liu, Zhi Li, Oengwang School of Information Science and Engineering Shandong University Jinan China Department of Radiation Oncology Shandong Tumor Hospital China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan China

ISBN: (纸本)9781424455386

A variety of wavelet transform methods have been introduced to remove noise from images. However, many of these algorithms remove the fine details and smooth the structures of the image when removing noise. The wavelet coefficient magnitude sum (WCMS) algorithm can preserve edges, but it is at the expense of removing noise. The Non-Local means algorithm can removing noise effective. But it tend to cause distortion (eg white). Meanwhile, when the noise is large, the method is not so effective. In this paper, we propose an efficient denoising algorithm. we denoised the image with non-local means algorithm in the spatial domain and WCMS algorithm in wavelet domain, weithted, combined them and got the image that we want. The experiment shows that our algorithm can improve PSNR form 0.6dB to 1.0dB and the image boundary is more clearly. © 2010 IEEE.

关键词： Wavelet transforms

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An efficient data indexing approach on Hadoop using Java persistence API

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作者： Lai, Yang Zhongzhi, Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100039 China

ISBN: (纸本)3642163262

Data indexing is common in data mining when working with high-dimensional, large-scale data sets. Hadoop, a cloud computing project using the MapReduce framework in Java, has become of significant interest in distributed data mining. To resolve problems of globalization, random-write and duration in Hadoop, a data indexing approach on Hadoop using the Java Persistence API (JPA) is elaborated in the implementation of a KD-tree algorithm on Hadoop. An improved intersection algorithm for distributed data indexing on Hadoop is proposed, it performs O(M+logN), and is suitable for occasions of multiple intersections. We compare the data indexing algorithm on open dataset and synthetic dataset in a modest cloud environment. The results show the algorithms are feasible in large-scale data mining. © 2010 IFIP.

关键词： Data mining

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Motor imagery classification based on the optimized SVM and BPNN by GA

Motor imagery classification based on the optimized SVM and ...

引用

International Conference on intelligent Control and Information processing (ICICIP)

作者： Yingying Jiao Xiaopei Wu Xiaojing Guo Key Laboratory of Intelligent Computing & Signal Processing MOE Anhui University Hefei China School of Computer Science and Technology Anhui University China

Brain-computer interface (BCI) is a specific Human-Computer interface in which the brain wave is employed as the carrier of control information. The ultimate goal of BCI is to build a direct communication pathway between human brain and external environment that does not depend on the limb mobility and language. In this paper, we carry out the experiment about the left or right hand motor imagery, and support vector machine with genetic algorithm (GA-SVM) and back propagation neural network with genetic algorithm (GA-BP) are employed to classify the μ rhythm evoked by movement imagination. The experiment results prove that GA-SVM can easily find out the appropriate parameters of SVM and GA-BP can avoid getting into local minimization to great extend. So higher accuracy of classification is achieved.

关键词： Support vector machines Classification algorithms Kernel Biological cells Accuracy Educational institutions Biological neural networks

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Application of AWE to scattering analysis of the double-negative medium (RCS) within a wider band.

Application of AWE to scattering analysis of the double-nega...

引用

第九届国际天线、电波传播及电磁理论学术研讨会(ISAPE2010)

作者： Mei Yang Yu-Xin Sun Hui Wang Ming-Sheng Chen Xian-liang Wu Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei Department of Physics and Electronic Engineering Hefei Normal University Hefei China School of In Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei

The PMCHWT equation of the double negative media (DNG) is obtained based on its constitutive relationship. And the surface currents and radar cross section (RCS) at a single frequency point is computed by Method of moments (MOM). The asymptotic waveform evaluation (AWE) technique for dispersive dielectric medium is deduced and apllied to electromagnetic scattering analysis of double-negative medium within a given frequency band.

关键词： Moment methods Optical propagation Silicon compounds

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Combining the missing link: An incremental topic model of document content and hyperlink

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作者： Ma, Huifang Li, Zhixin Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100080 Beijing China Graduate School of the Chinese Academy of Sciences 100039 Beijing China

ISBN: (纸本)3642163262

The content and structure of linked information such as sets of web pages or research paper archives are dynamic and keep on changing. Even though different methods are proposed to exploit both the link structure and the content information, no existing approach can effectively deal with this evolution. We propose a novel joint model, called Link-IPLSI, to combine texts and links in a topic modeling framework incrementally. The model takes advantage of a novel link updating technique that can cope with dynamic changes of online document streams in a faster and scalable way. Furthermore, an adaptive asymmetric learning method is adopted to freely control the assignment of weights to terms and citations. Experimental results on two different sources of online information demonstrate the time saving strength of our method and indicate that our model leads to systematic improvements in the quality of classification. © 2010 IFIP.

关键词： Websites

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