ANALYSIS OF WORD SEARCH ALGORITHMS IN THE DICTIONARIES OF MACHINE TRANSLATION SYSTEMS FOR ARTIFICIAL LANGUAGES

Abstract

The paper is devoted to the development of an organizational model of the machine translation system of artificial languages. The main goal is the analysis of word search algorithms in the dictionary, which are significant elements of the developed machine translation system at the stage of improvement of new dictionaries created on the basis of already existing dictionaries. In the course of the work was developed a model of the machine translation system, created dictionaries based on texts and based on already existing dictionaries using augmentation methods such as back translation and crossover; improved dictionary based on algorithms of n-grams, Knuth-Morris-Pratt and word search in the text (such as binary search, tree search, root decomposition search). In addition, the work implements the possibility of using the prepared dictionary for translation. The obtained results can improve existing systems of machine translation of the text of artificial languages. Namely, to reduce the operating time by approximately 20 times when switching from the balanced tree algorithm to other logarithmic algorithms. The practical significance of this work is the analysis and improvement of text augmentation algorithms using algorithms of binary search, hashes, search tree, and root decomposition.