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E-government affected by many factors, which contain highly complexity and uncertainty. While people definitely produce uncertain cognition from incomplete information, it is hard to use quantitative analysis for evaluating E-government performance. Therefore, this article attempts to use unascertained means cluster method to study the classification of E-government performance. Based on the analysis...
On the base of NS-IMMC, this paper propose a new method of generating the cause-and-effect of news topic. The new method choose representative sentences for news documents according to the specialty of news structure (NS, News structure), and then utilizes IMMC (Improved Min-Max clustering) to classify these representative sentences to generate multi-documents summary which represents the topic cause-and-effect...
In this paper, an ontology-based system for the agricultural FAQ retrieval was presented. A small pool of candidate question-answering pairs and sentence similarity were obtained using ontology-based automatic classification. The best performance was got based on splitted vector space model and semantic concept. The experiment was made to test the effect of the system. The satisfying results were...
Various feature extraction methods are developed in non-destructive evaluation (NDE). Among many linear methods been proposed, the Fisher linear discriminant is a very useful technique. But as the mean square error (MSE) increased, a classifier based on Fisher criterion will reduce the efficiency. In this paper, we expand the criterion and develop a spindle-deviation minimization (SDM) method to solve...
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