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A community mining algorithm for web texts based on Multi-agent system

Journal of computational Information Systems 2010年第11期6卷 3509-3516页

作者： Yang, Hui Wang, Zhe Zhou, Xu Zhou, Tong Wang, Zuo College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory for Symbol Computation and Knowledge Engineering Ministry of Education China

Most of the existing methods for community discovery only deal with social network with a fixed structure, so they can not effectively deal with dynamic social network. This paper proposes a Multi-agent system method which is applied to real-time dynamic web texts for community discovery. This method combines the multi-agent system control mechanisms with community discovery algorithm. The approach not only divides community for the published web text, but also changes the community division according to the newly updated contents of web texts. Meanwhile, the similarity of two web texts is evaluated through similarity algorithm which compares content similarity and semantic similarity. The effectiveness of this algorithm has been tested on real web texts networks and experiment 3 illustrated the scalability of our algorithm for dynamic community discovery of web texts. © 2010 Binary Information Press.

关键词： Semantics

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Optimization strategy of parallel query processing based on multi-core architecture

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Journal of Convergence Information Technology 2010年第8期5卷 24-24页

作者： Chen, Yongheng Zuo, Wanli He, Fengling Chen, Kerui College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

Chip Multi-Processor (CMP) could support more than two threads to execute simultaneously, and some executing units are owned by each core. Because threads share various resources of CMP, such as L2-Cache, among many threads, CMP system is inherently different from multiprocessors system and, CMP is also different from simultaneously multithreading (SMT). In this paper a novel and complete approach on how to parallelism for relational database multithreaded query execution that strives for maximum resource utilization for both CPU and disk activities. The focus of this approach is on how to use the multithreaded parallel technique to optimize and process queries based on multi-core architecture. A set of algorithms for implementing and optimizing the best query plan, such as the algorithms for scheduling and parallel executing the query plan, the algorithms for allocating thread to sub-query and memory to the buffers between operations in pipelining execution, are proposed in this method. Additionally this paper analysis and optimize the implementation of parallel buffers and multithread. In the experiments, this paper evaluates performance of the parallel buffers and tests the coordination of the multithread.

关键词： Scheduling algorithms

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A hybrid discrete PSO-SA algorithm to find optimal elimination orderings for Bayesian networks

A hybrid discrete PSO-SA algorithm to find optimal eliminati...

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2010 2nd International Conference on Industrial and Information Systems, IIS 2010

作者： Dong, Xuchu Ouyang, Dantong Cai, Dianbo Zhang, Yonggang Ye, Yuxin Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun Jilin China Network Monitor Maintenance Centre Jilin Branch China Telecom Corporation Limited Changchun Jilin China

ISBN: (纸本)9781424482177

In this paper, a hybrid algorithm named DPSO-SA is proposed to find near-to-optimal elimination orderings in Bayesian networks. DPSO-SA is a discrete particle swarm optimization method enhanced by simulated annealing. computational tests show that this hybrid method is very effective and robust for the elimination ordering problem. © 2010 IEEE.

关键词： Simulated annealing

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Cooperative coevolutionary genetic algorithms to find optimal elimination orderings for Bayesian networks

Cooperative coevolutionary genetic algorithms to find optima...

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Dong, Xuchu Yu, HaiHong Ouyang, Dantong Cai, Dianbo Ye, Yuxin Zhang, Yonggang Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun Jilin China Network Monitor Maintenance Centre Jilin Branch China Telecom Corporation Limited Changchun Jilin China

ISBN: (纸本)9781424464388

According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are proposed. Based on these works, six cooperative coevolutionary genetic algorithms are constructed. Numerical experiments show that these algorithms are more robust than other existing swarm intelligence methods when solving the elimination ordering problem. © 2010 IEEE.

关键词： Bayesian networks

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Analysis the uncertainties of the Ant Colony Algorithm

Analysis the uncertainties of the Ant Colony Algorithm

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International Conference on computational Aspects of Social Networks, CASON

作者： Zhang, Yi Zhang, Meng Cao, Xin-Yan Department of Information Engineer Jilin Business and Technology College Changchun 130062 China College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China College of Electronic Information Engineering University of Changchun Changchun Jilin Province 130000 China

ISBN: (纸本)9780769542027

In this paper, the subject of discussion is the uncertainties of Ant Colony Algorithm(ACA). In order to find application and popularize the ACA, we try to find some disciplinarians which can eliminate the impact of uncertainties in our algorithm and find the best assembled of the parameters by a series of experiments. Results show that our works had great effects in practicality. © 2010 IEEE.

关键词： Traveling salesman problem

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A Stable Stochastic Optimization Algorithm for Triangulation of Bayesian Networks

A Stable Stochastic Optimization Algorithm for Triangulation...

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International Workshop on knowledge Discovery and Data Mining (WKDD)

作者： Xuchu Dong Dantong Ouyang Yuxin Ye Shasha Feng Haihong Yu Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun Jilin China

ISBN: (纸本)9781424453979

In this paper, we present a novel deterministic heuristic and a new genetic algorithm to solve the problem of optimal triangulation of Bayesian networks. The heuristic, named MinFillWeight, aims to select variables minimizing the multiplication of the weights on nodes of fill-in edges. The genetic algorithm, named GA-MFW, uses a new rank-reserving crossover operator and a 2-fold mutation mechanism utilizing the MinFillWeight heuristic. Experiments on representative benchmark show that the deterministic heuristic and the stochastic algorithm have good performance and stability to various problems.

关键词： Stochastic processes Bayesian methods Tree graphs Ethics Genetic algorithms Inference algorithms Genetic mutations Stability Ant colony optimization Data mining

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A Multi-heuristic Cooperative Ant Colony System for Optimizing Elimination Ordering of Bayesian Networks

A Multi-heuristic Cooperative Ant Colony System for Optimizi...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Xuchu Dong Dantong Ouyang Yuxin Ye Haihong Yu Yonggang Zhang Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun Jilin China

To solve the problem of searching for an optimal elimination ordering of Bayesian networks, a novel effective heuristic, MinSum Weight, and an ACS approach incorporated with multi-heuristic mechanism are proposed. The ACS approach named MHC-ACS utilizes a set of heuristics to direct the ants moving in the search space. The cooperation of multiple heuristics helps ants explore more regions. Moreover, the most appropriate heuristic will be identified and be reinforced with the evolution of the whole system. Experiments demonstrate that MHC-ACS has a better performance than other swarm intelligence methods.

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Adaptive feature selection and extraction approaches for image retrieval based on region

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Journal of Multimedia 2010年第1期5卷 85-92页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Institute of Computer Graphics and Image Processing Dalian Nationalities University Dalian China State Key Laboratory of CAD and CG Zhejiang University Hangzhou China

Image retrieval based on region is one of the most promising and active research directions in recent year's CBIR, while region segmentation, feature selection and feature extraction of region are key issues. However, the existing approaches always adopt a uniform approach of segmentation and feature extraction for all images in the same system. In this paper, we propose adaptive image segmentation and feature extraction approach according to different category image for image retrieval system. To improve performance, we propose adaptive segmentation approach according to different category image. Textured image is segmented by Gaussian Mixture Models (GMM), while non-textured image is segmented by our proposed block-based normalized cut. To accurately describe feature of region, we propose weight assignment method for centroid pixel and its neighbor by convolution with normal distribution when image segmentation by GMM. To improve generalization, we propose adaptive number of Fourier descriptors of shape signature which depends on the energy distribution of Fourier descriptors, instead of fixed number by experience. To simply and efficiently describe the spatial relationships of multi-object or multi-region in same image, we apply simplified topological relationships. The experiments demonstrate that proposed approaches are superior to the traditional approaches. © 2010 ACADEMY PUBLISHER.

关键词： Feature extraction

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Describing the semantic relation of the deep web query interfaces using ontology extended LAV

Journal of Software

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Journal of Software 2010年第1期5卷 89-98页

作者： Liang, Hao Zuo, Wan-Li Ren, Fei Department of Computer Science and Technology Jilin University Jilin Changchun China Department of Information Changchun Taxation College Jilin Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

The key element in a Deep Web information fusion system is the data source modeling problem, which is the determinant technical factor of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of extracting attributes and semantic relationships from the interfaces utilizing Ontology is present in this paper, and WordNet is introduced as an Ontology instrument. The semantic relationships between semantic related attributes are evaluated by the WordNet. The meaningless attributes are instantiated by instance information embedded in the interfaces. A semantic matrix is generated and used to evaluate the semantic related groups in the specific domains. The expression ability of LAV is extended by the mapping and matching mechanism based on the semantic related groups. The experiment is carried out on the famous dataset, and the results show the efficiency of Ontology extended LAV of building mappings between local schemas and mediator schema. © 2010 ACADEMY PUBLISHER.

关键词： Ontology

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Mining data records based on ontology evolution for deep web

Mining data records based on ontology evolution for deep web

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International Conference on Computer engineering and Technology, ICCET

作者： Wen Zhang Kerui Chen Fan Zhang College of Information Engineering Zhongzhou University Zhengzhou China College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun China

ISBN: (纸本)9781424463473;9781424463497;9781424463503

Currently, the research for the extraction of information in deep web is pretty active. Although many researchers already adopted ontology in the data extraction, many problems still exist. This paper proposed an ontology evolution based method for mining in the data area. Not only will this method solve the problem when the website only consists of one record, but it also can identify he meaning of data that has no labels. With the evolution of ontology, the extraction of data records is being more accurate. Experiments indicate that this method could improve the accuracy and efficiency of data extraction.

关键词： Data mining Ontologies Entropy Educational institutions knowledge engineering Web pages Data engineering Random processes Computer science Educational technology

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