Many of the previous incremental methods in data streams are deleting the old patterns and adding to the new patterns directly, which may delete useful patterns too early. Both different real data and the data occurri...
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In order to process the software bug feature sequences, this paper presents a gap-constrained sequential pattern mining algorithm, MEMIGCSP algorithm. The length of the interval between items is limited in the origina...
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3-SPS+RRS+PS is a new type of mechanism. There is good application prospect in the field of aerospace. Especially some key kinetic characteristic calculation algorithms are implemented, which makes its calculation mec...
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The inuence maximization problem is defined as providing a given initial integer k, mining top-k inuential nodes from a social network such that the spread of inuence in the network is maximized. Some existing studies...
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The inuence maximization problem is defined as providing a given initial integer k, mining top-k inuential nodes from a social network such that the spread of inuence in the network is maximized. Some existing studies are based on Greedy algorithm, but their time complexity is very high. In this paper, a different method based on Genetic Algorithms, denoted as MAGA is proposed. In the MAGA algorithm, the set of k nodes is seen as a candidate solution, and the expected inuence value as fitness. Use the genetic algorithm to get the optimal solution. Experiments show that the algorithm achieved a balance in inuence spread and running time.
This paper discusses the simulated computation methods of remote sensing information model, and tries to put forward a more available solution. It presents our research works on the description and simulation methods ...
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Sequential pattern mining has a wide range of applications in data streams. The real data involves multiple data streams and each data stream is itemset-sequence. However, most algorithms mine a single item in a singl...
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In this paper, we proposed a new sequential pattern mining algorithm called WSPD for mining weighted sequential patterns in data streams. The algorithm produces no false negatives and places a bound on the error of th...
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Maximal frequent sequence mining is an important research issue which has realized the highly compressed storage of frequent sequences. At present, most algorithms are based on bottom-up method and large numbers of ca...
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The formal model of spatial directional relations is one of the most important parts in spatial relation research. The most of models are based on Minimum Bounding Rectangle (MBR), and they are not compliant with the ...
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The formal model of spatial directional relations is one of the most important parts in spatial relation research. The most of models are based on Minimum Bounding Rectangle (MBR), and they are not compliant with the regular pattern of human cognition. In order to get a closer conclusion to human cognition on directional relationship, Angle Histogram model based on Double-projection and Rounded-subdivision (AHDPRS) is proposed in this paper. The model uses the maximum inscribed circles to find out the maximum parts of the object, and calculates the directional relationship between the centers of the circles. This model ignores the inessential details to ensure the result which will be closer to human cognition. The experiments show that this model is feasible.
Since the SIFT feature point extraction algorithm with scale changes, rotation transformation invariance, is widely used in image registration. In this paper, the SIFT algorithm is applied to three-dimensional point c...
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Since the SIFT feature point extraction algorithm with scale changes, rotation transformation invariance, is widely used in image registration. In this paper, the SIFT algorithm is applied to three-dimensional point cloud coarse registration, the proposed 3DSIFT extraction algorithm is suitable for three-dimensional point cloud data, then point coordinates, curvature, the nearest neighbor distance mean and other information compose fourteen-dimensional vector to conduct correspondence match, use the interior point rate of Ransac to obtain optimal transformation, and finally transform the coordinates for source point clouds using the optimal transform, complete the point cloud data coarse registration. Experimental results show that our coarse registration algorithm can effectively extract feature points, and it is robust for the point cloud with noisy point, it can provide accurate and effective initial value for the precise registration such as ICP.
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