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International Conference on Fuzzy Systems and knowledge Discovery (FSKD)

作者： Zhili Pei Xiaohu Shi Maurizio Marchese Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China College of Mathematics & Computer Science National University of Inner Mongolia Tongliao China Department of Information and Communication Technology University of Trento Povo TN USA

The improvement of text categorization by statistical methods can be performed from two main directions, namely the feature selection and the evaluation of characteristic weights. In this paper, we propose an enhanced text categorization method based on a modified mutual information algorithm and evaluation algorithm of characteristic weights which improves both aspects. The proposed method is applied to the benchmark test set Reuters-21578 Top10 to examine its effectiveness. Numerical results show that the precision, the recall and the value of F1 of the proposed method are all superior to those of existing conventional methods.

关键词： Text categorization Mutual information Frequency shift keying Frequency estimation Computer science Statistical analysis Testing Educational institutions Communications technology Performance evaluation

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Effective pruning algorithm for least squares support vector machine classifier

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2007年第7期44卷 1128-1136页

作者： Yang, Xiaowei Lu, Jie Zhang, Guangquan School of Mathematical Sciences South China University of Technology Guangzhou 510641 China Faculty of Information Technology Sydney University of Technology NSW 2007 Australia Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Changchun 130012 China

A well-known drawback in the least squares support vector machine (LS-SVM) is that the sparseness is lost. In this study, an effective pruning algorithm is developed to deal with this problem. To avoid solving the primal set of linear equations, the bottom to the top strategy is adopted in the proposed algorithm. During the training process of the algorithm, the chunking incremental and decremental learning procedures are used alternately. A small support vector set, which can cover most of the information in the training set, can be formed adaptively. Using the support vector set, one can construct the final classifier. In order to test the validation of the proposed algorithm, it has been applied to five benchmarking UCI datasets. In order to show the relationships among the chunking size, the number of support vector machine, the training time, and the testing accuracy, different chunking sizes are tested. The experimental results show that the proposed algorithm can adaptively obtain the sparse solutions without almost losing generalization performance when the chunking size is equal to 2, and also its training speed is much faster than that of the sequential minimal optimization (SMO) algorithm. The proposed algorithm can also be applied to the least squares support vector regression machine as well as LS-SVM classifier.

关键词： Support vector machines

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An ontology-based method in information translation

An ontology-based method in information translation

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2nd International Conference on Semantics, knowledge, and Grid, SKG 2006

作者： Bai, Yan Liu, Dayou Open Symbol Computation and Knowledge Engineering Laboratory of State Education Ministry College of Computer Science and Technology Jilin University China

ISBN: (纸本)076952673X

An ontology-based method named AOBM is proposed in this paper. It fully takes into account the factors that will afect the communication, and using ontology can be represented in agent's knowledge base. Pmvided ontology did not belong to the public data or have any public ontology, AOBM establishes a layering algorithm, which is able to avoid logical exception handling policies, ensure the right understanding of the communication entity concept, and resolve the consistency problem of the concept translation. Experimental results show that AOBM is superior to other methods, and can effectively improve the communication consistency of a mobile agent system under certain conditions. © 2006 IEEE.

关键词： Ontology

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Graph-based fast image segmentation

Graph-based fast image segmentation

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Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, SSPR 2006 and SPR 2006

作者： Han, Dongfeng Li, Wenhui Lu, Xiaosuo Li, N. Wang, Yi Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)3540372369

In this paper, we describe a fast semi-automatic segmentation algorithm. A nodes aggregation method is proposed for improving the running time and a Graph-Cuts method is used to model the segmentation problem. The whole process is interactive. Once the users specify the interest regions by drawing a few lines, the segmentation process is reliably computed automatically no additional users' efforts are required. It is convenient and efficient in practical applications. Experiments are given and outputs are encouraging. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Image segmentation

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A novel method for mining sequential patterns in datasets

A novel method for mining sequential patterns in datasets

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ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications

作者： Xiaoyu, Chang Chunguang, Zhou Zhe, Wang Ping, Hu Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun 130012 China

ISBN: (纸本)0769525288

Sequential pattern mining is one of the most important fields in data mining. In this paper, we propose a novel algorithm FSPAN (Fast Sequential Pattern mining algorithm) to do the sequence mining. FSPAN can mine all the frequent sequential patterns in large datasets and it integrates a depth-first traversal approach with an effective pruning mechanism. This pruning mechanism solves the problem of searching frequent sequences in a sequence database by searching frequent items or frequent itemsets, which makes this method very efficient. Moreover, the databases scanned via FSPAN keep shrinking quickly, which makes the algorithm more efficient when the sequential patterns are longer. Experiments on standard test data show that FSPAN is very effective. © 2006 IEEE.

关键词： Data mining

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Combining greedy method and genetic algorithm to identify transcription factor binding sites

Combining greedy method and genetic algorithm to identify tr...

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6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006

作者： Wanyu, Wang Xiaoyu, Chang Chunguang, Zhou Key Laboratory of Symbol Computation and Knowledge Engineering Juin University Ministry of Education Changchun 130012 China

ISBN: (纸本)0769526624

Identification of Transcription Factor Binding Sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a novel approach to identify transcription factor binding sites. This approach combines greedy method and genetic algorithm (CGGA) to search conserved segment in the given sequence set. A new greedy method which can efficiently search a local optimal result is proposed. In order to solve the high complexity of this algorithm, we also give an effective improvement for this method. Then, we describe how to combine genetic algorithm with this greedy method to find the more optimal results. Greedy method is combined to the fitness function of the genetic algorithm. We apply this approach on two different TFBS sets and the results show that it can find correct result both effective and efficient, and for CRP binding sites, it get a more accurate result than Gibbs Sampler, AlignACE and MDGA. © 2006 IEEE.

关键词： Transcription factors

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An adaptive stochastic collision detection between deformable objects using particle swarm optimization

An adaptive stochastic collision detection between deformabl...

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EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC

作者： Tianzhu, Wang Wenhui, Li Yi, Wang Zihou, Ge Dongfeng, Han Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)3540332375

In this paper, we present an efficient method for detecting collisions between highly deformable objects, which is a combination of newly developed stochastic method and Particle Swarm Optimization (PSO) algorithm. Firstly, our algorithm samples primitive pairs within the models to construct a discrete binary search space for PSO, and in this way user can balance performance and detection quality. Besides a particle update process is added in every time step to handle the dynamic environments caused by deformations. Our algorithm is also very general that makes no assumptions about the input models and doesn't need to store additional data structures either. In the end, we give the precision and efficiency evaluation about the algorithm and find it might be a reasonable choice for complex deformable models in collision detection systems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Intelligent agents

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Modeling and refining directional relations based on fuzzy mathematical morphology

Modeling and refining directional relations based on fuzzy m...

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High-Power Diode Laser Technology and Applications IV

作者： Sun, Haibin Li, Wenhui Key Laboratory of Symbol Computation Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)0819461466

In this paper, we investigate the deficiency of Goyal and Egenhofer's method for modeling cardinal directional relations between simple regions and provide the computational model based on the concept of mathematical morphology, which can be a complement and refinement of Goyal and Egenhofer's model for crisp regions. Based on fuzzy set theory, we extend Goyal and Egenhofer's model to handle fuzziness and provide a computational model based on alpha-morphology, which combines fuzzy set theory and mathematical morphology, to refine the fuzzy cardinal directional relations. Then the computational problems are investigated. We also give an example of spatial configuration in 2-dimensional discrete space. The experiment results confirm the cognitive plausibility of our computational models. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Fuzzy sets

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Fast kernel for calculating structural information similarities

Fast kernel for calculating structural information similarit...

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3rd IEEE International Conference on Intelligent Systems

作者： Wei, Jin-Mao Wang, Shu-Qin Wang, Jing You, Jun-Ping Institute of Computational Intelligence Northeast Normal University Open Symbol Computation and Knowledge Engineering Laboratory of State Education Jilin University Changchun Jilin 130024 China School of Mathematics and Statistics Northeast Normal University Changchun Jilin 130024 China

ISBN: (纸本)9781424401956

Structural similarity computation plays a crucial role in many applications such as in searching similar documents, in comparing chemical compounds, in finding genetic similarities, etc. We propose in this paper to use structural information content (SIC) for measuring structural information, considering both the nodes and edges of trees. We utilize a binary encoding approach for assigning the weights of different layer nodes and determining if some tree is a subtree of another tree. By defining a fast kernel and recursively computing SICs, we evaluate the structural information similarities of data trees to pattern trees. In the paper, we present the algorithm for calculating SICs with computation complexity of O(n), and use simple examples to instantiate the performance of the proposed method..

关键词： structural information content structural similarity structural pattern analysis web mining

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Identification of transcription factor binding sites using GA and PSO

Identification of transcription factor binding sites using G...

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6th International Conference on Intelligent Systems Design and Applications (ISDA 2006)

作者： Chang, Xiao-Yu Zhou, Chun-Guang Li, Yan-Wen Hu, Ping Key Laboratory of Symbol Computation and J Knowledge Engineering Jilin University Ministry of Education China Department of Computer Science Northeast Normal University Changchun 130012 China

ISBN: (纸本)0769525288

Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under this framework, we use two prevalent evolutionary algorithms: Genetic, Algorithm (GA) and Particle Swarm Optimization (PSO) to find unknown sites in a collection of relatively long intergenic sequences that are suspected of being bound by the same factor. This paper represents binding sites motif to position weight matrix (PWM) and introduces how to code PWM to genome for GA and how to code it to particle for PSO. We apply these two algorithms to 5 different yeast Saccharomyces Cerevisiae transcription factor binding sites and CRP binding sites. The results on Saccharomyces Cerevisiae show that it can find the correct binding sites motifs, and the result on CRP shows that these two algorithms can achieve more accuracy than MEME and Gibbs Sampler.

关键词： Binding sites

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