A multiclass text categorization model based on latent semantic analysis and support vector machine is researched and designed to enhance the accuracy of categorization.

为了提高文本分类的准确性，研究并设计了一个基于潜在语义分析和支持向量机的多类文本分类模型。

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The proposed method was based on vector support machine of semantic space in which text and user profile were represented by the semantic space.

提出基于语义空间的支持向量机的文本过滤，用语义来表示文本和用户模板。

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This paper proposes a new Support Vector Machine(SVM) for anomaly intrusion detection method based on Latent Semantic Indexing(LSI).

论文提出了一种基于潜在语义索引（LSI）和支持向量机（SVM）的异常入侵检测方法。

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