利用这些计算余弦相似度的一个变种的概述在这里。
It USES those to compute a variant of cosine similarity outlined here.
它更多的是从这个矩阵的概念框架，和余弦相似度的概念出现。
The VSM is more of a conceptual framework from which this matrix, and the notion of cosine similarity arise.
这表明，计算余弦相似度，你只需要把那些文件，有一些术语通常与查询。
It follows that, to compute cosine similarity, you only need to consider those documents that have some term in common with the query.
如果你回顾余弦相似度的教科书的定义，你会发现它是在一个查询和文档的相应术语权重的产品的总和，归一化。
If you review the textbook definition of cosine similarity, you'll find that it's the sum of products of corresponding term weights in a query and a document, normalized.
通过沿时间轴对采样信号加窗的方式构造向量集合，利用余弦相似度进行向量间亲合度的匹配计算，实现在实数域进行匹配计算的实数值负向选择算法。
The matching affinity between two vectors was measured using cosine similarity to develop a real-valued negative selection algorithm with the matching calculation in the real domain.
方法将色谱指纹图谱看作多维空间内的向量，利用向量夹角余弦的基本公式计算两个指纹图谱间的相似度；
METHODS Chromatogram can be treated as vector of hyperspace, and the similarity between them can be counted according to vectorial angle formula.
相似度匹配方法的研究结果表明余弦距离分类器分类效果最佳。
Studying of similarity match methods, it shows that cosine distance is best for classification.
将HPLC指纹图谱看作多维空间内的向量，利用向量夹角余弦的基本公式计算两个指纹图谱间的相似度。
HPLC curves was treated as vector of hyperspace, the similarity between them was calculated by using the cosine value of the Angle between them.
用骨架语片做特征项，用空间向量模型表示文本语义，用语片的出现频度做语片权重，用余弦法计算文本间语义相似度。
Computing the semantic similarity of sentences by the method of cosine, eigenvalue come from the skeleton semantic clip, and the semantics of sentence expressed the vector space model.
中药指纹图谱相似度的影响因素由样品所含的主要化学成分所引起 ，相关系数法比夹角余弦法对指纹图谱中小色谱峰变化的反应明显。
The important influence factors to TCMF are due to the difference of the main contents of TCM, the Cosin method is better for similarity evaluation than Correlation method.
中药指纹图谱相似度的影响因素由样品所含的主要化学成分所引起 ，相关系数法比夹角余弦法对指纹图谱中小色谱峰变化的反应明显。
The important influence factors to TCMF are due to the difference of the main contents of TCM, the Cosin method is better for similarity evaluation than Correlation method.
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