{'fraction_non_alphanumeric': 0.020872865275142316, 'fraction_numerical': 0.0, 'mean_word_length': 5.719745222929936, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Knowledge Transformation via Different Structures of Concepts and its Application in Argumentation Theory and Case-Based Reasoning

The article is devoted to solving some problems of argumentation theory and case-based reasoning. For this purpose, we develop methods for transforming knowledge presented in various structures of concepts. The correspondence rules between concepts of different levels of generality are investigated. We use formal concept lattices to assess knowledge and test the equivalence of knowledge transformations. Based on Melchuk's theory “Meaning <=> text”, formal methods of extracting knowledge from natural language texts and representing the extracted knowledge are proposed. To formally represent domain case structures, we modify the predicates by adding special situation-constants to them. The concept of ontological homomorphism of algebraic systems is introduced, on the basis of which the similarity of cases is defined. These constructions are used to develop argumentation structures that use case-based reasoning.