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 ...
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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 t...
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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.
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....
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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 prop...
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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 un...
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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 mi...
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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.
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...
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.
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. Howe...
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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 t...
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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 onto...
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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.
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