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。
A multiclass text categorization model based on latent semantic analysis and support vector machine is researched and designed to enhance the accuracy of categorization.
前置词的机用语义词典描述可为俄语文本语义分析提供必要的计算资源。
The formalization of prepositional meaning can offer necessary calculation resources for the automatic Russian text analysis.
从语义推理技术入手，主要针对描述逻辑、推理算法和推理机三个方面进行了研究分析。
Starting from the semantic inference technology, the authors research and analyze from three mainly aspects, including description logic, inference algorithm and inference engine.
一个脚本引擎通常包括的组件有：符号表、词法分析器、语法分析器、语义检查器、中间代码生成器、代码优化器、代码生成器、虚拟机。
The script engine has some components, include symbol table, lexical analyzer, parser, semantic checker, intermediate code generator, optimizer, code generator, virtual machine.
一个脚本引擎通常包括的组件有：符号表、词法分析器、语法分析器、语义检查器、中间代码生成器、代码优化器、代码生成器、虚拟机。
The script engine has some components, include symbol table, lexical analyzer, parser, semantic checker, intermediate code generator, optimizer, code generator, virtual machine.
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