AUTOMATIC TEXT TRANSLATION ALGORITHM USING THE WORLD MODEL TREE
The paper describes an approach to modeling human learning by constructing a graph of a world model using the example of teaching a system to translate from one natural language to another. Building a model of the world is made automatically based on the processing of an array of pairs of texts in the input and output languages. The approach is based on the representation of the situation described in the input text as a subtree of the general model of the world in the input language. From this subtree in the input language, select the subtree of the world model in the output language. The subtree in the output language is converted into plain text, which is the translation of the source text.