Deep web could automatically produce web pages according to the query criteria of users. The report found most query result page store data information using table form. knowledge management, information retrieval, We...
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Deep web could automatically produce web pages according to the query criteria of users. The report found most query result page store data information using table form. knowledge management, information retrieval, Web mining, abstract extraction and so on were benefited from automatically understanding of table forms. The study web forms on the web information extraction and integration have important significance. This paper proposed a domain-specific ontology based strategy for integration tables, and this method could independent the structure of table. Experimental results confirm that this method could effectively improve the accuracy of integration.
Collective classification, which is represented to classify unobserved nodes simultaneously in networked data is becoming an important research area with applications in several domains, such as the classification of ...
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Collective classification, which is represented to classify unobserved nodes simultaneously in networked data is becoming an important research area with applications in several domains, such as the classification of documents, image processing. Most algorithms are based on the hypothesis that nearby nodes tend to have the same label. However, there are many networks that do not necessarily satisfy this hypothesis. In this paper, we present a new method based on random walk and link pattern of the network. It adopts the pseudoinverse laplacian matrix of the graph as similarity measure to identify nearby nodes and assigns an initial label for each unlabeled node, then iteratively update the label of unlabeled nodes based on the link pattern. The experimental results on two real world datasets demonstrate that the proposed method outperforms the other state-of-art approaches for this problem.
Community mining has been the focus of many recent researches on dynamic social networks. In this paper, we propose a clustering based improved ant colony algorithm (CIACA) for community mining in social networks. The...
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Community mining has been the focus of many recent researches on dynamic social networks. In this paper, we propose a clustering based improved ant colony algorithm (CIACA) for community mining in social networks. The CIACA combines the local pheromone update rule with the global update rule and utilizes heuristic function to adjust the clustering solution dynamically, assisted by decay coefficient of dynamic network model. In order to improve clustering accuracy and convergence rate in the process of ant migration, a structure tightness between nodes based clustering centers initializing method is proposed, which can provide us initial clustering centers with certain clustering precision and high diversity. In addition, random number and specific parameter are used in the ant transition probability, which strengthens the search stochastic properties of CIACA effectively. The proposed CIACA is tested on some benchmark social networks, and is compared with current representative algorithms in community mining. Experimental results show the feasibility and validity of CIACA.
This paper presents a novel representation and matching method for deformable shapes. The proposed approach finds most expressive segments of a deformable shape category called similar and discriminative parts, which ...
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A novel constant tamper-proofing software watermark technique based on H encryption function is presented. First we split the watermark into smaller pieces before encoding them using CLOC scheme. With the watermark pi...
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The reconfigurable design problem is to find the element that will result in a sector pattern main beam with side lobes. The same excitation amplitudes apply to the array with zero-phase that should be in a high direc...
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The reconfigurable design problem is to find the element that will result in a sector pattern main beam with side lobes. The same excitation amplitudes apply to the array with zero-phase that should be in a high directivity, low side lobe pencil shaped main beam. Multi-beam antenna arrays have important applications in communications and radar. This paper presents a new method of designing a reconfigurable antenna array with quantized phase excitations using a new evolutionary algorithm called differential evolution (DE). In order to reduce the effect of mutual coupling among the antenna-array elements, the dynamic range ratio is minimized. Additionally, compared with the continuous realization and subsequent quantization, experimental results indicate better performance of the discrete realization of the phase-excitation value of the proposed algorithm.
Image retrieval has been an active research topic due to its great importance in the field of image management, digital library and web searching. However, the performances of the existing approaches, including text-b...
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Recently evolutionary search has been investigated by lots of researchers as method for structure learning of Bayesian network. In order to avoid the problem of premature convergence and enhance the learning accuracy,...
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Recently evolutionary search has been investigated by lots of researchers as method for structure learning of Bayesian network. In order to avoid the problem of premature convergence and enhance the learning accuracy, in this paper we integrated evolutionary way of bees and proposed triple-population evolution strategies to learn Bayesian network structure. During evolution, the best Bayesian network individual is considered as queen bee, and there are three populations: one stores and evolves elitist individuals, another stores random individuals to guarantee the diversity of individuals, some individuals from that two populations form the third population in which every individual is considered as drone and mated with queen bee to generate offspring. The proposed method has both exploitative and explorative ability. Experimental results show that the proposed method can converge to more accurate Bayesian network than standard genetic algorithm based learning method.
Bayesian network is a popular tool for uncertainty process in Artificial Intelligence. In recent years, more and more attention has been paid to learning of Bayesian network. In this paper, we proposed a novel learnin...
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Bayesian network is a popular tool for uncertainty process in Artificial Intelligence. In recent years, more and more attention has been paid to learning of Bayesian network. In this paper, we proposed a novel learning algorithm for Bayesian network based on (μ, λ)-Evolution Strategy, we present the encoding scheme and fitness function, designed the evolutionary operators of recombination, mutation and selection. Theoretical analysis and experimental results all demonstrate that the proposed method can learn the Bayesian network from data effectively.
An automatic system to detect cracks of solar cells on satellite solar panel through camera has been proposed in this study. And a novel binarization method based on gray intensity wave transformation is also introduc...
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An automatic system to detect cracks of solar cells on satellite solar panel through camera has been proposed in this study. And a novel binarization method based on gray intensity wave transformation is also introduced to decrease the impact of non-uniform illumination on cell image. It adaptively classifies the pixel depending on local peak and trough on the gray intensity surface. After the cell image binareized, a strategy called “adjacency searching” is adopted to remove the gate lines. Then the ellipse fitting based on least squares is conducted on the contours of crack segments to get their angles, which are used to connect these segments into the whole crack. The experiment on 5000 cells in one panel had shown that the precision of our system has reached 98.5%, and its false alarm rate is less than 9%, which could meet the application requirements.
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