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13th International World Wide Web Conference on Alternate Track, Papers and Posters, WWW Alt. 2004

作者： Zhuge, Hai Zheng, Liping Zhang, Nan Li, Xiang China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)1581139128

An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for constructing the semantic link network. The basic premise of this work is that the semantics of a web page can be reflected by a set of keywords, and the semantic relationship between two web pages can be determined by the semantic relationship between their keyword sets. The approach adopts the data mining algorithms to discover the semantic relationships between keyword sets, and then uses deductive and analogical reasoning to enrich the semantic relationships. The proposed algorithms have been implemented. Experiment shows that the approach is feasible.

关键词： Data mining

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Modeling the growth of future web1 13

Modeling the growth of future web1

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13th International World Wide Web Conference on Alternate Track, Papers and Posters, WWW Alt. 2004

作者： Zhuge, Hai Chen, Xue Li, Xiang China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)1581139128

The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from the network. Through establishing and investigating two types of models for such a network, we obtain the same scale free distribution of semantic links. Simulations and comparisons validate the rationality of the proposed models.

关键词： Semantic Web

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Greedy EM algorithm for robust t-mixture modeling

Greedy EM algorithm for robust t-mixture modeling

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International Conference on Image and Graphics (ICIG)

作者： Sibao Chen Haixian Wang Bin Luo Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China

This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to determine how to insert new component. The greedy algorithm obviates the complicated initialization. The results are comparable to that of split-and-merge EM algorithm while the proposed algorithm is faster. Also the by product of a sequence of mixture models is useful for model selection. Experiments of synthetic data clustering and unsupervised color image segmentation are given.

关键词： Robustness signal processing algorithms Clustering algorithms Tail Greedy algorithms Convergence Gaussian distribution Color Image segmentation Probability distribution

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Journal of Information Science and Engineering: Editorial notice

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Journal of Information Science and Engineering 2005年第5期21卷 i-ii页

作者： Lee, Der-Tsai Amato, Nancy M. Chang, Shih-Fu Chen, Homer H. Chen, Tsuhan Hsu, Tsan-Sheng Hwang, Jenq-Neng Kuo, Sy-Yen Kuo, Tei-Wei Li, Chung-Sheng Tokuyama, Takeshi Wing, Jeannette Wu, Tzong-Chen Yen, John Computer Science at Texas A and M University United States Parasol Laboratory United States IEEE Transactions on Parallel and Distributed Systems Computing Research Association's Committee on the Status of Women in Computing Research CRA-W's Distributed Mentor Program United States Department of Electrical Engineering Columbia University United States Lab. United States College of Electrical Engineering and Computer Science National Taiwan University Taiwan IEEE Transactions on Circuits and Systems for Video Technology IEEE Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States ACM ACM SIGACT IEEE Computer Society IICM Austria Research and Development of the Department Multimedia Signal Processing Technical Committee IEEE Signal Processing Society United States IEEE Transactions on Circuits and systems for Video Technology College of Electrical Engineering and Computer Science National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan IEEE Technical Committee on Real-Time Systems Computer Science Division IBM T.J. Watson Research Center United States IBM Research Division Graduate School of Information Sciences Tohoku University Japan ACM IPSJ Mathematical Society of Japan Japan Department of Computer Science Computer Science Department Carnegie Mellon University United States National Academies of Science's Computer Science and Telecommunications Board United States Microsoft's Trustworthy Academic Advisory Board Intel Research Pittsburgh's Advisory Board United States Dartmouth's Institute for Security Technology Studies Advisory Committee Canada Sloan Research Fellowships Program Committee United States ACM Taiwan China Information Sciences and Technology Pennsylvania State University United States Laboratory for Intelligent Agents Penn State's School of Info

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Rough set based image texture recognition algorithm

Rough set based image texture recognition algorithm

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8th International Conference on Knowledge-Based intelligent Information and Engineering Systems, KES 2004

作者： Zheng, Zheng Hu, Hong Shi, Zhong Zhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate School of the Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783540301325

Rough set theory is emerging as a new tool for dealing with fuzzy and uncertain data. In recent years, it has been successfully applied in such fields as machine learning, data mining, knowledge acquiring, etc. In this paper, rough set theory is applied to image texture recognition. Based on rough set and generalized approximate space, we develop a rough set based image texture recognition algorithm. We compare it with some other algorithms and the results show that our algorithm is effective and efficient. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Image texture

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A stereo matching algorithm based on multiresolution and epipolar constraint

A stereo matching algorithm based on multiresolution and epi...

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International Conference on Image and Graphics (ICIG)

作者： Wei Zhang Quanbing Zhang Lei Qu Sui Wei Key Laboratory of Intelligence Computing and Signal Processing Anhui University Hefei Anhui China

Stereo matching is one of the most active research areas in computer vision. In this paper, a fast stereo matching algorithm by means of epipolar constraint and multiresolution approach was presented. The searching scope of corresponding pixels in the original image is obtained and has diminished a lot based on multiresolution approach. Then intensity correlation principle and epipolar constraint can be applied to get the stereo matching results in this scope. In this way, we reduce the search time for correspondence and ensure the validity of matching. The experimental results show this algorithm is effective and efficient.

关键词： Stereo vision signal processing algorithms signal resolution Computer vision Pixel Image resolution Cameras Geometry Image analysis Distortion measurement

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A Fast Recursive Total Least Squares Algorithm for Adaptive FIR Filtering

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IEEE Transactions on signal processing 2004年第10期52卷 2729-2737页

作者： Feng, Da-Zheng Zhang, Xian-Da Chang, Dong-Xia Zheng, Wei Xing Key Laboratory for Radar Signal Processing Xidian University 710071 Xi'an China Department of Automation Key State Laboratory of Intelligent Technique and Systems Tsinghua University Beijing 100084 China General Software Laboratory Institute of Software Chinese Academy of Science Beijing China School of QMMS University of Western Sydney Sydney NSW 1797 Australia

This paper proposes a new fast recursive total least squares (N-RTLS) algorithm to recursively compute the TLS solution for adaptive finite impulse response (FIR) filtering. The N-RTLS algorithm is based on the minimization of the constrained Rayleigh quotient (c-RQ) in which the last entry of the parameter vector is constrained to the negative one. As analysis results on the convergence of the proposed algorithm, we study the properties of the stationary points of the c-RQ. The high computational efficiency of the new algorithm depends on the efficient computation of the fast gain vector (FGV) and the adaptation of the c-RQ. Since the last entry of the parameter vector in the c-RQ has been fixed as the negative one, a minimum point of the c-RQ is searched only along the input data vector, and a more efficient N-RTLS algorithm is obtained by using the FGV. As compared with Davila's RTLS algorithms, the N-RTLS algorithm saves the 6M number of multiplies, divides, and square roots (MADs). The global convergence of the new algorithm is studied by LaSalle's invariance principle. The performances of the relevant algorithms are compared via simulations, and the long-term numerical stability of the N-RTLS algorithm is verified. © 2004, IEEE. All rights reserved.

关键词： Adaptive filtering fast gain vector finite impulse response global convergence Rayleigh quotient total least squares

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Robust t-mixture modelling with SMEM algorithm

Robust t-mixture modelling with SMEM algorithm

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Si-Bao Chen Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui University of Science and Technology Hefei China

ISBN: (纸本)0780384032

Multivariate t-mixture modelling is more robust than Gaussian mixture modelling to a set of data containing a group or groups of observations with longer than Gaussian tails or a typical observations. To alleviate the problem of local convergence of the traditional EM algorithm, a split-and-merge operation is introduced into the EM algorithm for multivariate t-mixtures. The split-and-merge equations are first presented theoretically and then a new merge method is acquired. Accordingly, a modified EM algorithm is constructed. Experiments of data clustering and unsupervised color image segmentation are given.

关键词： Robustness Clustering algorithms signal processing algorithms Image segmentation Parameter estimation Gaussian distribution Probability density function Covariance matrix Tail Equations

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ULMM: A uniform logic modeling method in intelligent tutoring systems

ULMM: A uniform logic modeling method in intelligent tutorin...

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8th International Conference on Knowledge-Based intelligent Information and Engineering Systems, KES 2004

作者： Si, Jinxin Cao, Cungen Sui, Yuefei Yue, Xiaoli Xie, Nengfu Knowledge Acquisition and Sharing Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100080 China The Graduate School of the Chinese Academy of Sciences China

ISBN: (纸本)9783540301325

More researchers recognize that it is an emergent and important issue that intelligent tutoring mechanism can be depicted, evaluated and measured on the uniform theoretical foundation which should be a highly formalized and computerized model in order to explore ITSs and advance effective and efficient cross-reference, fusion and integration among diverse intelligent tutoring models and systems. This paper proposes a novel uniform logic modeling method from an associative viewpoint and highlights the concrete formal models of three core elements (i.e. knowledge model, student model and pedagogical strategy model) in the architecture of an ITS. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Computer aided instruction

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The Application of Digital Human in Distance Education

The Application of Digital Human in Distance Education

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The 8th International Conference on Computer Supported Cooperative Work in Design(第八届计算机支持的协同工作设计国际会议)(CSCWD2004)

作者： Liyan Liu Fucang Jia Hua Li Zongkai Lin Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100080

ISBN: (纸本)0780379411

Digital Human is a booming research area andits combination with distance education will greatlypromote the advances of medicine, anatomy andother relevant disciplines, ht this paper they areintegrated to establish a local-network baseddistance education experimental system whichcontains functions such as teaching, practicing,tutoring and discussing, etc. The volume of thedigital human datasets is too huge to be dealt withtraditional centralized storing methods, so the gridtechnology is introduced to provide an efficient, safeand transparent management of the mass *** this experiment our solution is proved tobe valid and feasible.

关键词： distance learning computer aided instruction teaching medicine grid computing virtual reality biomedical education digital human distance education medicine anatomy teaching tutoring grid technology transparent data management

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