In this paper, the defects latent semantic analysis, probabilistic latent semantic analysis using methods to construct the text-the words of co-occurrence matrix, using the em algorithm to solve.
本文针对潜在语义分析存在的缺陷，采用概率潜在语义分析的方法构造文本——词语的同现矩阵，使用EM算法进行迭代求解。
This paper presents methods of mechanical matching, feature lexicon, binding matrix, grammar analysis and semantic understanding for the Chinese language automatic word segmentation.
本文给出了为汉语自动分词而提出的机械匹配法、特征词库法、约束矩阵法、语法分析法和理解切分法。
In this paper, we use the co-occurrence path to explain the relationship between the index words and extract the semantic information in the term-term matrix to expand the query.
本文首先利用传递度来量化索引词与索引词间的关联关系，然后利用索引词与索引词的关系矩阵中存在的语义关系对查询向量进行智能扩展。
The semantic relationships between multi-context key words are taken into account and the fuzzy similarity matrix is derived from non-distance computing in this method.
该方法不仅考虑了多背景关键词之间的语义关系，而且通过非距离计算得到模糊相似矩阵。
Then, we propose an image classification method based on feature complement ratio matrix, which tries to bridge the semantic gap from two aspects.
接着，本文提出了一种基于特征互补率矩阵的图像分类方法，试图从两个角度减小语义鸿沟。
Then, we propose an image classification method based on feature complement ratio matrix, which tries to bridge the semantic gap from two aspects.
接着，本文提出了一种基于特征互补率矩阵的图像分类方法，试图从两个角度减小语义鸿沟。
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