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2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： XIAO-WEI CHEN QI-SONG CHEN XIN ZHANG SHI-HUAN XIONG College of Computer Science and Technology Guizhou University Guiyang 550025 China GuiZhou Key Laboratory for Photoelectric Technology and Application Guiyang 550025 China Mathematics and Computer Science Department of Guizhou Education College Guiyang 550003 China

Chaotic time series analysis or forecasting is an important and complex problem in machine learning. As an effective tool, support vector machine (SVM) has been broadly adopted in pattern recognition and machine learning fields. In developing a successful SVM classifier, eliminating noise and extracting feature are very important This paper proposes the application of kernel PCA to LS-SVM for feature extraction. Then PSO algorithm is employed to optimization of these parameters in LS-SVM. The novel chaotic time series analysis model integrates the advantages of wavelet transform, KPCA, PSO and LS-SVM. Compared with other predictors, this model has greater generality ability and higher accuracy.

关键词： KPCA PSO SVM Feature eztraction Prediction model

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Research on the method of entity homepage recognition

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Journal of Computational Information Systems 2009年第6期5卷 1617-1624页

作者： Li, Lina Yu, Zhengtao Zou, Junjie Su, Lei Xian, Yantuan Mao, Cunli The School of Information Engineering and Automation Kunming University of Science and Technology Kunming 650051 China The Institute of Intelligent Information Processing Computer Technology Application Key Laboratory of Yunnan Province Kunming 650051 China School of Software Yunnan University Kunming 650091 China

Entity Homepage Recognition(EHR) is an important part of entity finding. In this paper, a method of EHR based on AdaBoost is proposed. With the help of Google, this method recalls pages related to answer entities and recognizes to obtain the relevant entity homepage. In detail, Person, Organization and Product, three types of entities are analyzed respectively and 3148 entities and the corresponding entity homepages are collected, besides, on the basis of entity characteristic, we define the entity features related to the features of link and webpage content, as well as, these features are extracted to form a training data set;And then using different learning algorithms with different features to identify the homepage to find the most effective classification features and homepage recognition learning algorithm. Experiments were done by employing the test data set of entity task in TREC-2009 and the method of 10-fold cross validation, the results show the best effects have been achieved by adopting the method of AdaBoost, specifically, combined with the features of link and webpage content, the recognition accuracy rate for right homepage reaches 91.34%. 1553-9105/ Copyright © 2009 Binary Information Press.

关键词： Adaptive boosting

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Transmission capacities for overlaid spread-spectrum wireless networks

Transmission capacities for overlaid spread-spectrum wireles...

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IEEE International Conference on Communications technology and applications, ICCTA

作者： Di Li Changchuan Yin Huarui Wu Yan Ma Jianfeng Li Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing China Department of Computer Application National Engineering Research Center for Information Technology in Agriculture China Research Institute of Networking Technology Beijing University of Posts and Telecommunications China

In this paper, the transmission capacities of two coexisting wireless networks (primary network and secondary network) in the same geographic region and sharing the same spectrum are derived. The primary (PR) network has a higher priority to access the spectrum, while the secondary (SR) network limits its interference to the PR network by controlling its transmission intensity. Considering spread-spectrum transmission, frequency hopping (FH-CDMA) and direct sequence (DS-CDMA), we derive the transmission capacities for PR and SR networks, which incorporate no spreading as a special case. Extend our results in Refs. [1,2] to a more general case. Our results show that the sum transmission capacity of the two networks (i.e., the overall spectrum efficiency per unit area) is boosted significantly over that of a single network, and the transmission capacity gain is larger than that of no spreading case.

关键词： Spread spectrum communication Wireless networks

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A parallel optimization model for massive data stream application

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Ruan Jian Xue Bao/Journal of Software 2009年第SUPPL. 1期20卷 23-33页

作者： Sun, Xiao-Juan Sun, Ning-Hui Lei, Bin Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics The Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Computer System and Architecture Institute of Computing Technology The Chinese Academy of Sciences Beijing 100190 China

While computing is entering a new phase in which CPU improvements are driven by the addition of multiple cores on a single chip, rather than higher frequencies. Parallel processing on these systems is in a primitive stage, and requires the explicit use and knowledge of underlying thread architecture. Based on the features of massive data stream application, this paper proposes three-level pipelining programming model of multithreading system, which realizes the new synchronization mechanism with no contention of shared structures and is capable to provide differential service for data streams. Then the paper applies the new model to remote sensing information processing system and backbone network intrusion detection system, and evaluates the improved system on several multicore platforms. In performance analysis, the optimized effects of backbone network intrusion detection system are evaluated in several aspects of throughput scalability on both SPARC T1 and x86 platforms, the impacts of different multithreading mapping methods on throughput, and the comparison of response time and service quality before and after optimization. The experimental results show that the system throughput has good scalability on both platforms, the values of response time are greatly improved and the prioritized streams achieve better response time with the differential service mechanism. © by Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Metadata

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Research on high rate USB storage system interface based on DM642 for H.264 standard stream media files

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Journal of Information and Computational Science 2008年第2期5卷 687-694页

作者： Chen, Qisong Zhang, Xin Chen, Xiaowei Wang, Guomei College of Computer Science and Technology Guizhou University Guiyang 550025 China Guizhou Key Laboratory for Photoelectric Technology and Application Guiyang 550025 China

Video files suffer serious damage during transmission and storage for the great capacity. How to transmit and store video files is a hot issue for the researchers in this field. This paper proposes a novel method to design high rate USB2.0 interface, and implements it in transmission and storage stream media files based on H.264 standard. Compared with MPEG-4 and other previous standards, H.264, the current video standard has achieved great breakthrough in coding performance. But the complexity of H.264 encoder is still very high. The main task in this paper is to design and implement the special USB2.0 interface for high rate to transmit and store H.264 stream media files. The optimization and implementation of H.264 baseline profile encoder on the TMS320DM642 has been presented. Based on the architectural features of TMS320DM642, the H.264 encoder has been optimized from three aspects: algorithms, data transfer and memory/Cache use. So the optimized H.264 encoder can achieve an encoding speed of more than 24 frames per second. On this basis, chip CY7C68013 is set in GPIF mode as the USB interface controller, then the integrity system is available. The actual running results show this controller has excellent rate performances and robustness against external disturbances, it can be expanded easily and support hot swap operation.

关键词： Data transfer

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Retrieval-oriented summarization

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Journal of Computational Information Systems 2008年第5期4卷 2237-2244页

作者： Li, Weijiang Zhao, Tiejun Zang, Wenmao Computer Application Key Laboratory of Yunnan Province Kunming University of Science and Technology Kunming 650051 China School of Computer Science Haerbin Institute of Technology Harbin 150001 China

This paper presents an investigation into the utility of document summarization in the context of information retrieval. The investigation explores the use of both context-independent standard summaries and query-biased summaries. We developed a generic, a query-based, and a hybrid summarizer, each with differing amounts of document context. The generic summarizer used a blend of discourse information and information obtained through traditional surface-level analysis. We evaluate these summaries through summary-based retrieval models proposed by author on several TREC collections. We show that it is worse that retrieval documents with summaries directly. However, summary-based retrieval model, smoothing document model with summary model, can perform consistently across collections of realistic size, and significant improvements over document-based retrieval can be obtained in a fully automatic manner and without relevance information provided by human. © 2008 Binary Information Press.

关键词： Information retrieval

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Apical-dominant particle swarm optimization

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Progress in Natural Science:Materials International 2008年第12期18卷 1577-1582页

作者： Zhihua Cui~(a,b) Xingjuan Cai~b Jianchao Zeng~b Guoji Sun~a a State key laboratory for Manufacturing Systems Engineering,Xi’an Jiaotong University,Xi’an 710049,China b Division of System Simulation and computer application,Taiyuan University of Science and technology,Taiyuan 030024,China [a]State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Xi’an 710049 China [b]Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan 030024 China

Particle swarm optimization (PSO) is a new stochastic population-based search methodology by simulating the animal social behaviors such as birds flocking and fish *** improvements have been proposed within the framework of this biological assumption. However,in this paper,the search pattern of PSO is used to model the branch growth process of natural *** provides a different poten- tial manner from artificial *** illustrate the effectiveness of this new model,apical dominance phenomenon is introduced to construct a ncvel variant by emphasizing the influence of the *** this improvement,the population is divided into three different kinds of buds associated with their ***,a mutation strategy is applied to enhance the ability escaping from a local ***- ulation results demonstrate good performance of the new method when solving high-dimensional multi-modal problems.

关键词： Apical-dominance phenomenon Particle swarm optimization Branch growth model High-dimensional multi-modal benchmarks

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Multivariate classification of deep web sources based on maximum entropy model

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Journal of Computational Information Systems 2008年第3期4卷 1093-1100页

作者： Huang, Li Zhao, Pengpeng Cui, Zhiming Wei, Fang Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China

With the fast development of World Wide Web, the quantity of web information is increasing in an unprecedented pace, a great many of which are generated dynamically from background databases, and can't be indexed by traditional search engine, so we call them Deep Web. For the heterogeneous and dynamic features of Deep Web sources, classifying the Deep Web source by domain effectively is a significant precondition of Deep Web sources integration. In this paper, we consider the visible features of Deep Web and Maximum Entropy approach, and then on the basis of binary classification, we propose a new multivariate classification approach based on Maximum Entropy towards Deep Web sources. In addition, we propose a Feedback algorithm to improve the accuracy of classification. An experimental evaluation over real Web data shows that, our approach could provide an effective and general solution to the multivariate classification of Deep Web sources.

关键词： Search engines

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Restricted-domain question classification with the help of syntactic structures relationships and domain characteristic

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Journal of Computational Information Systems 2008年第6期4卷 2659-2665页

作者： Meng, Xiangyan Yu, Zhengtao Zhang, Cheng Li, Yingwei Guo, Jianyi Mao, Cunli School of Information Engineering and Automation Kunming University of Science and Technology Kunming 650051 China Computer Technology Application Key Laboratory of Yunnan Province B The Institute of Intelligent Information Processing Kunming 650051 China

Question classification is an important step in a question answering system, the accuracy rate of question classification has great impact to a question answering system's following module. This paper proposed a question classification method which union syntactic structures relationships and domain characteristic. This method chooses sentence trunk and domain terms as classified characteristic, uses improved Bayes classify learning algorithm to structure question classification model. This paper has realized question classification in Yunnan tourism question answering system. Experiment results showed that the method is effective;the accuracy rate is 87.4% in 5 coarse and 79.5% in 23 fine in Yunnan traveling domain. © 2008 Binary Information Press.

关键词： Syntactics

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Forecasting system based on Wavelet Transform and PSO-SVM

Forecasting system based on Wavelet Transform and PSO-SVM

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IEEE International Workshop on Anti-counterfeiting, Security, Identification, ASID

作者： Qisong Chen Yun Wu Xin Zhang Xiaowei Chen School of Computer Science and Technology Guizhou University Guiyang Guizhou China GuiZhou Key Laboratory for Photoelectric Technology and Application Guiyang Guizhou China

A new method for load forecasting based on LS-SVM, PSO and wavelet transform is proposed. The wavelet transform is adopted to decompose the historical data, so the approximate part and several detail parts are obtained. The results of wavelet transform are predicted by a separate LS-SVM predictor. PSO is employed to determine these parameters of SVM model. The novel forecast model integrates the advantage of WT, PSO and LS-SVM. Compared with other predictors, this forecast model has greater generality ability and higher accuracy.

关键词： Wavelet transforms Load forecasting Discrete wavelet transforms Predictive models Autoregressive processes computer science Support vector machines Least squares methods Particle swarm optimization Stochastic processes

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