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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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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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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An active e-course is a self-representable and self-organizable document mechanism with a flexible structure. The kernel of the active e-course is to organize learning materials into a "concept space" rather...
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ISBN:
(纸本)1581139128
An active e-course is a self-representable and self-organizable document mechanism with a flexible structure. The kernel of the active e-course is to organize learning materials into a "concept space" rather than a "page space". Besides highly interactive service, it supports adaptive learning by dynamically selecting, organizing and presenting the learning materials for different students. During the learning progress, it also provides assessments on students' learning performances and gives suggestions to guide them in further learning. We have implemented an authoring tool and a course prototype to support the constructivist learning.
Traditional 1-best translation pipelines suffer a major drawback: the errors of 1- best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeline. In order to alleviate this probl...
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Traditional 1-best translation pipelines suffer a major drawback: the errors of 1- best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeline. In order to alleviate this problem, we use compact structures, lattice and forest, in each module instead of 1-best results. We integrate both lattice and forest into a single tree-to-string system, and explore the algorithms of lattice parsing, lattice-forest-based rule extraction and decoding. More importantly, our model takes into account all the probabilities of different steps, such as segmentation, parsing, and translation. The main advantage of our model is that we can make global decision to search for the best segmentation, parse-tree and translation in one step. Medium-scale experiments show an improvement of +0.9 BLEU points over a state-of-the-art forest-based baseline.
Curvelet transform is the combination of the multi-scale analysis and multi-directional analysis transforms, which is more suitable for objects with curves. Applications of the curvelet transform have increased rapidl...
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Thinning algorithms can be classified into two general types: serial and parallel algorithms. Several algorithms have been proposed, but they have limitations. A new thinning algorithm based on the centroid of the blo...
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Previous work using topic model for statistical machine translation (SMT) explore topic information at the word level. However, SMT has been advanced from word-based paradigm to phrase/rule-based paradigm. We therefor...
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Standard backprojection technique is used in typical through-wall synthetic aperture radar (TWSAR) image, it implicitly assumes infinite beamwidth, whereby the entire target area is illuminated and returns are collect...
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