The thesis presents a semantic vector algorithm, builds up the network of image semantic keywords, and realizes the composite retrieval of the image low-level feature and semantics characteristics.
提出了一种语义向量算法，构建了图像语义关键词网络，实现了图像底层视觉特征和语义的复合索引。
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。
Using latent semantic analysis to extract feature, the affect of synonymy and polysemy in text representation process is eliminated and the dimension of text vector is reduced.
利用潜在语义分析进行特征抽取，消除多义词和同义词在文本表示时造成的偏差，并实现文本向量的降维。
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