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。
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.
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。
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.
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.
针对群决策中专家给出的关于方案两两比较的语言判断矩阵，给出一种基于二元语义的群决策方法。
With respect to the linguistic pairwise judgment matrices on alternatives provided by experts in group decision making, a decision analysis method based on two tuple is proposed.
研究了二元语义判断矩阵的一致性问题。
The consistency of two-tuple linguistic judgement matrix is studied.
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。
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.
该算法能基于双语语料，通过机器学习来自动进行语义聚类，生成词间相似度矩阵。
Based on bilingual corpora, the algorithm can produce words-similarity-matrix through machine learning.
针对具有不同粒度语言判断矩阵形式偏好信息的群决策问题，提出了一种基于二元语义信息处理的群集结与方案优选方法。
With regard to a kind of multiple attribute group decision making problems with linguistic assessment information, a new approach to group aggregation and alternative selection is proposed.
针对具有不同粒度语言判断矩阵形式偏好信息的群决策问题，提出了一种基于二元语义信息处理的群集结与方案优选方法。
With regard to a kind of multiple attribute group decision making problems with linguistic assessment information, a new approach to group aggregation and alternative selection is proposed.
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