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International Conference on Machine Learning and Cybernetics

作者： He, Qing Li, Ning Shi, Zhong-Zhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Hebei University Baoding 071002 Hebei China Graduate University of Chinese Academy of Sciences Hebei University Baoding 071002 Hebei China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei China

ISBN: (纸本)9781424465262

Support Vector Machine (SVM) is a classification technique of machine learning based on statistical learning theory. A quadratic optimization problem needs to be solved in the algorithm, and with the increase of the samples, the time complexity will also increase. So it is necessary to shrink training sets to reduce the time complexity. A sample selection method for SVM is proposed in this paper. It is inspired from the Hyper surface classification (HSC), which is a universal classification method based on Jordan Curve Theorem, and there is no need for mapping from lower-dimensional space to higher-dimensional space. The experiments show that the algorithm shrinks training sets keeping the accuracy for unseen vectors high. © 2010 IEEE.

关键词： Support vector machines

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Risk analysis of system security based on evidence theory

Risk analysis of system security based on evidence theory

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2010 International Conference on Computer Design and Applications, ICCDA 2010

作者： Xu, Peida Xu, Jianling Deng, Yong Su, Xiaoyan Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai China Grain Economics Institute Nanjing University of Finance and Economics Nanjing China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Hanzhou Zhejiang China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Shanghai China

ISBN: (纸本)9781424471638

Risk evaluation is very important to the design and improvement of physical protection systems. In this paper, an evaluation method of multi-source information fusion is proposed based on the D-S evidence theory. In the proposed method, each individual component of the protection system in the simulated plane is modeled. Then, the threat report of each component according to the specific tactics is determined based on its real environment. Finally, the comprehensive threat distribution is obtained based on through the D-S evidence theory to combine multi-sources information. The proposed method can easily applied to the evaluation of the effectiveness of the protection system. We make the total threat of the protection system lowest through changes of the protection resources allocation. A numerical example is used to illustrate the efficiency of the proposed method. © 2010 IEEE.

关键词： information fusion

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From Use Case Model to Service Model An Environment Ontology Based Approach

From Use Case Model to Service Model An Environment Ontology...

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The Ninth International Conference on Grid and cloud computing(第九届网格与云计算国际学术会议 GCC 2010)

作者： Guangjun Cai Bin Zhao Zhi Jin Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Graduate Unive Software Engineering Institute Peking University Beijing China

One fundamental problem in services computing is how to bridge the gap between business requirements and various heterogeneous IT services. This involves eliciting business requirements and building a solution accordingly by reusing available services. While the business requirements are commonly elicited through use cases and scenarios, it is not straightforward to transform the use case model into a service model, and the existing manual approach is cumbersome and error-prone. In this paper, the environment ontology, which is used to model the problem space, is utilized to facilitate the model transformation process. The environment ontology provides a common understanding between business analysts and software engineers. The required software functionalities as well as the available services’ capabilities are described using this ontology. By semi-automatically matching the required capability of each use case to the available capabilities provides by services, a use case is realized by that set of services. At the end of this paper, a fictitious case study was used to illustrate how this approach works.

关键词： services computing requirements engineering use case environment ontology service model

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Automatic video genre categorization and event detection techniques on large-scale sports data 10

Automatic video genre categorization and event detection tec...

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Proceedings of the 2010 Conference of the Center for Advanced Studies on Collaborative Research

作者： Zhang, Ning Duan, Ling-Yu Huang, Qingming Li, Lingfang Gao, Wen Guan, Ling Ryerson Multimedia Research Laboratory Ryerson University Toronto ON Canada Institute of Digital Media Peking University Beijing 100871 China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate University of Chinese Academy of Sciences Beijing 100190 China

This paper presents an efficient and robust automatic process for large-scale sports video analysis. The proposed system firstly identifies the genre of the query video, and then accomplishes the interesting event detection task. The significance of this framework is its automatic characteristic in testing with minimum human involvement in training, as well as the scalability and expansibility in dealing with a large-scale dataset. Domain-knowledge independent local features are extracted from an input video sequence and a histogram based distribution representation is created using the bag-of-visual-words (BoW) model. In genre categorization, k-nearest neighbor (k-NN) classifiers with various dissimilarity measures are assessed and evaluated analytically. For the event detection, a hidden conditional random field (HCRF) structured prediction model is utilized. Overall, this framework demonstrates the efficiency and accuracy in processing voluminous data from sports collection and achieves various tasks in video analysis. It also demonstrates a potential technology transformation from the "laboratory bench" to commercial applications. © 2010 Ning Zhang, Ling-Yu Duan, Qing-ming Huang, Lingfang Li, Wen Gao and Ling Guan.

关键词： Sports

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Better filtration and augmentation for hierarchical phrase-based translation rules

Better filtration and augmentation for hierarchical phrase-b...

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48th Annual Meeting of the Association for Computational Linguistics, ACL 2010

作者： Wang, Zhiyang Lü, Yajuan Liu, Qun Hwang, Young-Sook Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China HILab Convergence Technology Center C and i Business SKTelecom 11 Euljiro2-ga Jung-gu Seoul 100-999 Korea Republic of

ISBN: (纸本)9781617388088

This paper presents a novel filtration criterion to restrict the rule extraction for the hierarchical phrase-based translation model, where a bilingual but relaxed wellformed dependency restriction is used to filter out bad rules. Furthermore, a new feature which describes the regularity that the source/target dependency edge triggers the target/source word is also proposed. Experimental results show that, the new criteria weeds out about 40% rules while with translation performance improvement, and the new feature brings another improvement to the baseline system, especially on larger corpus. © 2010 Association for Computational Linguistics.

关键词： Translation (languages)

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Rate-distortion optimized transform for intra-frame coding

Rate-distortion optimized transform for intra-frame coding

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Xin Zhao Li Zhang Siwei Ma Wen Gao Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Institute of Digital Media Peking University Beijing China

In this paper, a novel algorithm is proposed for intra-frame coding, named as rate-distortion optimized transform (RDOT). Unlike existing intra-frame coding schemes where the transform matrices are either fixed or mode dependent, in the proposed algorithm, transform is implemented with multiple candidate transform matrices. With this flexibility, for coding each residual block, the encoder is endowed with the power to select the optimal transform matrix in terms of rate-distortion tradeoff. The proposed algorithm has been implemented in the latest ITU-T VCEG-KTA software. Experimental results show that, over a wide range of test set, the proposed method achieves average 0.43dB coding gain compared with the recent Mode-Dependent Directional Transform (MDDT). The improvement is more significant at high bit-rates, and up to 1dB coding gain can be achieved.

关键词： Transforms Encoding Image coding IP networks Training Decoding Gain

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A Bigtree Index for Resource Space Model

A Bigtree Index for Resource Space Model

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Sixth International Conference on Semantics,Knowledge and Grids(第六届语义、知识与网格国际会议 SKG 2010)

作者： Zhongyi Zeng Hai Zhuge Department of Computer Science and Technology University of Science & Technology of China HefeiChi Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing

This paper presents the Bigtree, which is a hierarchical index for implementing the Resource Space Model.

关键词： Semantics Indexes Data models Humans USA Councils Springs Space technology

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Risk analysis of physical protection system based on evidence theory

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Journal of information and Computational Science 2010年第13期7卷 2871-2878页

作者： Xu, Peida Su, Xiaoyan Wu, Jiyi Sun, Xiaohong Zhang, Yajuan Deng, Yong College of Computer and Information Sciences Southwest University Chongqing 400715 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University Zhejiang 310036 China College of Food Science and Technology Shanghai Ocean University Shanghai 201306 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China Key Subject Laboratory of National defense for Radioactive Waste and Environmental Security Southwest University of Science and Technology Mianyang 621010 China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 200240 China

关键词： information fusion

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Automatically organize web text resources with frequent term tree

Automatically organize web text resources with frequent term...

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IEEE 9th International Conference on Computer and information Technology, CIT 2009

作者： Wang, Xiaofeng Shi, Zhongzhi Key Lab. of Intelligent Information Processing Institute of Computing Technology Graduate University of Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769538365

With the expansion of the Web, automatically organizing large scale text resources, e.g. Web pages, becomes very important. Many Web sites, like Google and Yahoo, use hierarchical classification trees to organize text resources in Web. User can easily find the text resources that meet their requirements by navigating these hierarchical classification trees. Typically, the text resources in Web are manually assigned to the nodes of the hierarchical classification tree. This limits the hierarchical classification tree to organize large scale text resources. In this paper, we propose a Frequent Term Tree to improve the ability of hierarchical classification tree in organizing large scale text resources in Web. Different from the Fp-tree [17] which is utilized to efficiently discover frequent patterns, the frequent term tree is used to organize resources with frequent pattern based classification. The Frequent Term Tree can accurately assign text resources to each node of classification tree and improve the ability in organizing resources with the incremental classified text resources. The evaluation of the Frequent Term Tree demonstrates that Frequent Term Tree can effectively and efficiently organize text resources. © 2009 IEEE.

关键词： Websites

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A new population diversity model in intelligence optimization algorithms

A new population diversity model in intelligence optimizatio...

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2009 International Conference on Computational Intelligence and Security, CIS 2009

作者： Feng, Jiqiang Xie, Weixin Xu, Chen Key Lab. for Intelligent Information Processing Shenzhen University Shenzhen China Institute of Intelligent Computing Science Shenzhen University Shenzhen China

ISBN: (纸本)9780769539317

A mathematical framework based on probability theory is presented that enables us to analyze one important aspect of SI algorithms: the population diversity. Firstly the population density degree is defined for the population in the SI algorithms. The population diversity is then discussed from the point of view of the normal distribution in statistics. We show that there is a close connection between the distribution and population diversity and that the essential structure of population diversity is quite similar to that of the distribution. A detailed construction of the population diversity model is then given that is based on probability distributions. The paper concludes with a generic numerical example that validates the population diversity model. © 2009 IEEE.

关键词： Normal distribution

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