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相似性测度的英文

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"相似性测度"怎么读用"相似性测度"造句

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  • similarity measure

例句与用法

  • Review of watermarking techniques for 3d polygonal models
    基于力学的多边形相似性测度方法
  • Similarity measure between shapes based on spatial fuzzy representation
    基于空间模糊化表示的图形相似性测度
  • This paper gave a recipe distance measurement method and recipe class distance measurement method based on hybrid variables measurement
    建立了配方的相似性测度及配方类间混合距离测度方法。
  • Two approaches to evaluating the performance of this similarity measure and the comparison with standard cosine vector similarity measure are also described
    进一步给出了对基于本体的相似性测度方法进行效果评价的2种策略以及该方法与经典余弦向量测度方法的比较结果。
  • To improve document clustering , a document similarity measure based on cosine vector and keywords frequency in documents is proposed , but also with an input ontology
    为了改进文本聚类的效果,提出了将领域知识本体和文本关键词词频相结合的基于余弦向量的文本相似性测度方法。
  • In this thesis we analyse this situation . then we normalized the mutual information , which testified an overlap invariant measure , so we use normalized mutual information ( nmi ) as a new similarity measure
    通过与其它几种相似性测度的比较,该方法对图像重叠区域的变化具有不变性,从而使配准更具鲁棒性。
  • When dealing with multimodality medical images , we investigated the best matching parameters by applying mutual information as the similarity measure and hybrid optimization algorithm as the search strategy
    对于多模医学图像,以互信息作为相似性测度,使用混合优化算法搜索出最佳配准变换参数,将待配准图像进行变换,从而达到配准的目的。
  • Mutual information algorithm use mutual information as a new matching criterion to measure the statistical dependence between the image intensities of corresponding pixels in both images , which is assumed to be maximal if the images are geometrically aligned
    互信息法则把信息论中的互信息作为衡量两幅图象配准的相似性测度函数,假设当两幅图象配准时,互信息达到最大值。
  • The ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology , and by means of semantic knowledge . the ontology can improve the effects of document similarity measure and feedback of information retrieval systems
    该本体面向特定领域,将关键词以不同权值对应于各分类类目,通过其语义知识来改进文本相似性测度以及信息检索系统的效果。
  • A method that combines category - based and keyword - based concepts for a better information retrieval system is introduced . to improve document clustering , a document similarity measure based on cosine vector and keywords frequency in documents is proposed , but also with an input ontology . the ontology is domain specific and includes a list of keywords organized by degree of importance to the categories of the ontology , and by means of semantic knowledge , the ontology can improve the effects of document similarity measure and feedback of information retrieval systems . two approaches to evaluating the performance of this similarity measure and the comparison with standard cosine vector similarity measure are also described
    介绍了一种综合各层级分类类目和对应关键词来构造概念体系并用于改进信息检索系统效果的方法.为了改进文本聚类的效果,提出了将领域知识本体和文本关键词词频相结合的基于余弦向量的文本相似性测度方法.该本体面向特定领域,将关键词以不同权值对应于各分类类目,通过其语义知识来改进文本相似性测度以及信息检索系统的效果.进一步给出了对基于本体的相似性测度方法进行效果评价的2种策略以及该方法与经典余弦向量测度方法的比较结果
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