系统分析了自然语言建模问题

D. S. Suleimanov, A. Fridman, Rinat A. Gilmullin, B. Kulik
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摘要

对自然语言(NL)建模问题的系统分析,使我们有可能阐明用这种语言积累和处理知识的现代手段效率低下的根本原因。这是此类工具智能化的复杂性,这些工具是在原始人工编程语言的基础上创建的,这些语言实际上代表了反射分析语言的子集或基于它们的人工结构。为了降低识别问题的严重程度,提出了基于语言化和感知识别的技术工具构建自然语言建模系统。这些工具包括NL词汇和语法手段的符号学模型。这种方法似乎特别适用于黏性语言;它应该以鞑靼语为例来实现。
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System analysis of the natural language modeling problem
System analysis of the problem of modeling a natural language (NL) made it possible to formulate the root cause of the low efficiency of modern means for accumulating and processing knowledge in such languages. This is the complexity of intellectualization for such tools, which are created on the basis of primitive artificial programming languages that practically represent a subset of flectional analytical languages or artificial constructions based on them. To reduce the severity of the identified problem, it is proposed to build NL modeling systems on the basis of technological tools for verbalization and recognition of sense. These tools consist of semiotic models of NL lexical and grammatical means. This approach seems to be especially promising for agglutinative languages; it is supposed to be implemented on the example of the Tatar language.
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