CONSTRUCTIVE-SYNTHESIZING MODELING OF NATURAL LANGUAGE TEXTS

V. Shynkarenko, I. Demidovich
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Abstract

Means for solving the problem of establishing the natural language texts authorship were developed. Theoretical tools consist of a constructors set was developed on the basis of structural and production modeling. These constructors are presented in this work. Some results of experimental studies based on this approach have been published in previous works by the author, the main results should be published in the next ones. Constructors developed: converter of natural language text into tagged, tagged text into a formal stochastic grammar and the authors style similarity degree establishment of two natural language works based on the coincidence of the corresponding stochastic grammars (their substitution rules). The proposed approach makes it possible to highlight the semantic features of the author's phrases construction, which is a characteristic of his speech. Working with a sentence as a unit of text to analyze its construction will allow you to more accurately determine the author's style in terms of the use of words, their sequences and characteristic language constructions. Allows not to be attached to specific parts of speech, but reveals the general logic of building phrases.
自然语言文本的建构-合成建模
为解决确定自然语言文本作者身份的问题开发了各种手段。理论工具包括一套基于结构和生产模型开发的构造函数。本作品介绍了这些构造函数。基于这种方法的一些实验研究结果已在作者以前的作品中发表,主要结果将在下一部作品中发表。 所开发的构造函数包括:将自然语言文本转换为标记文本、将标记文本转换为正式随机语法,以及根据相应随机语法(其替换规则)的重合度确定两篇自然语言作品的作者风格相似度。 所提出的方法可以突出作者遣词造句的语义特征,这也是作者说话的一个特点。将句子作为一个文本单元来分析其结构,可以更准确地确定作者在用词、语序和语言结构特征方面的风格。可以不拘泥于具体的语篇,而是揭示构建短语的一般逻辑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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