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检索条件"机构=The Key Laboratory of Intelligent Information Processing Institute of Computing Technology"
3326 条 记 录,以下是3221-3230 订阅
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Preferential walk: Towards efficient and scalable search in unstructured peer-to-peer networks  05
Preferential walk: Towards efficient and scalable search in ...
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14th International World Wide Web Conference, WWW2005
作者: Zhuge, Hai Chen, Xue Sun, Xiaoping Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China
To improve search efficiency and reduce unnecessary traffic in Peer-to-Peer (P2P) networks, this paper proposes a trust-based probabilistic search algorithm, called preferential walk (P-Walk). Every peer ranks its nei... 详细信息
来源: 评论
Some marginal learning algorithms for unsupervised problems
Some marginal learning algorithms for unsupervised problems
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IEEE International Conference on Intelligence and Security Informatics, ISI 2005
作者: Tao, Qing Wu, Gao-Wei Wang, Fei-Yue Wang, Jue Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China
In this paper, we investigate one-class and clustering problems by using statistical learning theory. To establish a universal framework, a unsupervised learning problem with predefined threshold η is formally descri... 详细信息
来源: 评论
Fisher score based naïve Bayesian classifier
Fisher score based naïve Bayesian classifier
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2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
作者: Zhongzhi, Shi Youping, Huang Sulan, Zhang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Science Beijing 100039 China
The naïve Bayesian classifier (NBC) is a simple yet very efficient classification technique in machine learning. But the unpractical condition independence assumption of NBC greatly degrades its performance. Ther... 详细信息
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Parallel web spiders for cooperative information gathering
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4th International Conference on Grid and Cooperative computing - GCC 2005
作者: Luo, Jiewen Shi, Zhongzhi Wang, Maoguang Wang, Wei Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences PO Box 2704-28 Beijing 100080 China Graduate School of Chinese Academy of Sciences
Web spider is a widely used approach to obtain information for search engines. As the size of the Web grows, it becomes a natural choice to parallelize the spider's crawling process. This paper presents a parallel... 详细信息
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A fast nondominated sorting algorithm
A fast nondominated sorting algorithm
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2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05
作者: Chuan, Shi Ming, Chen Zhongzhi, Shi Key Laboratory of Intelligent Information Process Institute of Computing Technology Chinese Academy of Science Graduate University Chinese Academy of Sciences
The process of nondominated sorting is one of main time-consuming parts of multiobjective evolutionary algorithm (MOEA). Designing a fast nondominated sorting algorithm is crucial to improve the performance of MOEA. T... 详细信息
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R-Chord: A semantic-Based peer data management model
R-Chord: A semantic-Based peer data management model
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1st International Conference on Semantics, Knowledge and Grid, SKG 2005
作者: Liu, Jie Zhuge, Hai Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences China
The key issue of Peer Data Management Systems (PDMSs) is how to efficiently organize and manage distributed resources in P2P networks to accurately route queries from the peer initiating the query to appropriate peers... 详细信息
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A method for constructing G1 continuous splines via matrix decomposition
A method for constructing G1 continuous splines via matrix d...
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9th International Conference on Computer Aided Design and Computer Graphics, CAD/CG 2005
作者: Luhong, Diao Hua, Li Zongmin, Li Chinese Academy of Sciences Institute of Computing Technology Key Lab. of Intelligent Information Processing Beijing China Chinese Academy of Sciences Graduate School Beijing China
Analysis of transforming matrices between Bezier basis functions and geometrically continuous basis functions is presented It is shown that G 2 transforming matrix has some relationship with G1 transforming matrix. Ba... 详细信息
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An analysis of current computational emotion models and systems
An analysis of current computational emotion models and syst...
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2nd Indian International Conference on Artificial Intelligence, IICAI 2005
作者: Zhan, Donglei Cao, Cungen Pan, Yu Wang, Haitao Yong, Xi Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 10080 Beijing China Graduate School Chinese Academy of Sciences 100039 Beijing China
Emotion study is a multi-disciplinary research subject. In the past three decades, a number of theoretical models of emotion and computer applications have been proposed from different perspectives including psycholog... 详细信息
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A novel feature extraction algorithm
A novel feature extraction algorithm
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International Conference on Machine Learning and Cybernetics, ICMLC 2005
作者: Ding, Shi-Fei Shi, Zhong-Zhi Wang, Yun-Cheng Li, Shu-Shan College of Information Science and Engineering Shandong Agricultural University Taian 271018 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China College of Information Science and Engineering Shandong University of Science and Technology Qingdao 266510 China
Feature extraction or selection is one of the most importmant steps in pattern recognition or pattern classification, data mining, machine learning and so on. In this paper, we introduce the information theory, propos... 详细信息
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information feature analysis and improved algorithm of PCA
Information feature analysis and improved algorithm of PCA
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International Conference on Machine Learning and Cybernetics, ICMLC 2005
作者: Ding, Shi-Fei Shi, Zhong-Zhi Liang, Yong Jin, Feng-Xiang College of Information Science and Engineering Shandong Agricultural University Taian 271018 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China College of Geo-Information Science and Engineering Shandong University of Science and Technology Qingdao 266510 China
Principal component analysis (PCA) is an important method in multivariate statistical analysis, and its main idea is compression of dimensionality including variables and samples. In this paper, based on the ideas con... 详细信息
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