APPLYING CLUSTER ANALYSIS OF EDUCATIONAL CONTENT FOR IDENTIFYING SIMILAR DOCUMENTS

Abstract

Research was conducted on the intellectual support of the process for improving the quality of the educational content forming professional competencies of higher education programs. At the same time, the identification of relevant working curricula of disciplines, taking into account the context of entities in documents with automatic extraction of entities and relations between them, has allowed to implement it without laborious processing and adaptation of knowledge bases. The subject of the study is the content of working curricula (syllabus), which are defined as a set of data that characterize the results of training and the content of the discipline. As a result of the work [1], the author created a corpus of texts from the documents of working curricula in the disciplines of the specialty "Information Systems". Existing approaches to the intellectual support of the formation of educational programs based on ontological models of systems [2-4] based on knowledge and rules, heuristic algorithms for the automated compilation of curricula, methods of expert assessments and cognitive maps do not allow to effectively take into account and quickly track changes in the market labor, and also in the space of educational content. In turn, the formation and actualization of ontological models, systems of rules and precedents by experts for all existing subject areas the preparation of educational programs is an extremely labor-intensive process that requires the involvement of a representative composition of experts in each of the subject areas to ensure the required accuracy.