Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content s...
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A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the ...
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In this paper, a unique road contour extraction approach from high resolution satellite image is proposed, in which the road contour was extracted in two steps. Firstly, support vector machines (SVM) was employed mere...
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In this paper, a unique road contour extraction approach from high resolution satellite image is proposed, in which the road contour was extracted in two steps. Firstly, support vector machines (SVM) was employed merely to classify the image into two groups of categories: a road group and a non-road group. The identified road group images are the discrete and irregularly distributed sampled points, and they are an uncompleted data set for the road. Secondly, the road contour was extracted from the road group images using the tensor voting framework, since the tensor voting technique is superior to the traditional methods in extracting the geometrical structure from the uncompleted data set. The experimental results on the high resolution satellite image demonstrate that the proposed approach worked well with images comprised by both rural and urban area features.
The Resource Space Model (RSM) is a semantic data model based on orthogonal classification semantics for effectively managing various resources in interconnection environment. In parallel with the integrity theories o...
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Linear classifiers are of great significance in the classification field. In this paper, with meticulous studies on the linear classifiers, we gained a general framework for constructing fast trained linear classifier...
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To improve search efficiency and reduce unnecessary traffic in Peer-to-Peer (P2P) networks, this paper proposes a trust-based probabilistic search algorithm, called preferential walk (P-Walk). Every peer ranks its nei...
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ISBN:
(纸本)1595930515
To improve search efficiency and reduce unnecessary traffic in Peer-to-Peer (P2P) networks, this paper proposes a trust-based probabilistic search algorithm, called preferential walk (P-Walk). Every peer ranks its neighbors according to searching experience. The highly ranked neighbors have higher probabilities to be queried. Simulation results show that P-Walk is not only efficient, but also robust against malicious behaviors. Furthermore, we measure peers' rank distribution and draw implications.
The key issue of Peer Data Management Systems (PDMSs) is how to efficiently organize and manage distributed resources in P2P networks to accurately route queries from the peer initiating the query to appropriate peers...
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Analysis of transforming matrices between Bezier basis functions and geometrically continuous basis functions is presented It is shown that G 2 transforming matrix has some relationship with G1 transforming matrix. Ba...
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The Knowledge Grid is an intelligent and sustainable Internet application environment that enables people and roles to effectively capture, publish, share and manage explicit knowledge resources. As an important funct...
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The Semantic Link Network model SLN and Resource Space Model RSM are semantic models proposed separately for effectively specifying and managing versatile resources across the Internet. Collab.rating the relational se...
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