在语境框架的基础上，设计实现了文本相似度计算算法。
Based on the Context Framework, the se-mantic frame of text is designed and the algorithm of computing semantic frame is developed.
文本相似度的计算在数字图书馆系统里有着广泛的应用前景。
It has a broad prospect to compute text similarity in terms of the digital library system.
通过利用基于词频的权值计算，同时改进传统文本相似度计算概率模型，改进SVM算法实现邮件过滤系统。
We can use term frequency to have a weighted calculation and improve traditional text similarity calculation probability model in SVM algorithm.
传统KNN方法的明显缺陷是样本相似度的计算量很大，使其在具有大量高维样本的Web文本分类中缺乏实用性。
The traditional KNN has a fatal defect that time of similarity computing is huge. The practicality will be lost when the KNN is applied to WEB text categorization with high dimension and huge samples.
传统KNN方法的明显缺陷是样本相似度的计算量很大，使其在具有大量高维样本的Web文本分类中缺乏实用性。
The traditional KNN has a fatal defect that time of similarity computing is huge. The practicality will be lost when the KNN is applied to WEB text categorization with high dimension and huge samples.
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