Yahimovich O. Information technology of searching keywords based on parsing English texts

The qualification research is dedicated to developing the informational technology of searching keywords based on the automation process of parsing English texts. The model of searching keywords has been improved, which, unlike the existing ones, is based on the information evaluation of parsing text results and takes into account the results of analysis of relationships between lexical units of text, which allowed to formalize the quality criterion of searching keywords process. For the first time, searching keywords method has been developed, which, unlike the existing ones, is based on finding syntactic relationships between word forms in sentences of English text with the help of technological capabilities of parsing of modern linguistic packages. The proposed method allows to improve the numerical characteristics of searching keywords quality, namely completeness and accuracy. The method of reducing the impact of verbal noise for searching keywords has been improved, which, unlike the existing ones, is based on the Stanford classification of relationships between lexical units of a sentence, which has improved the quality of results of searching keywords compared to the main method. The information technology of searching keywords has been further developed, which, unlike the existing ones, takes into account additional information of sentence parsing processes within the bounds of the consistent use of the two proposed methods, which allowed to refine numerical estimates of content parameters of the text and improve the quality of searching keywords. The practical value of the results obtained in the qualification research paper is as follows: formal description of the method of searching keywords in the English text, creating an algorithm for its implementation and developing software that finds keywords based on significant relationships between word forms in sentences of the English text and subsequent filtering of verbal noise.