Automatized Generation of Personalized Learning Paths through Aspects in Multidimensional Spaces

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

Establishing Correspondences between Attribute Spaces and Complex Concept Spaces Using Meta-PGN Classifier

In this paper, we present one approach for extending the learning set of a classification algorithm with additional metadata. It is used as a base for giving appropriate names to found regularities. The analysis of correspondence between connections established in the attribute space and existing links between concepts can be used as a test for creation of an adequate model of the observed world. Meta-PGN classifier is suggested as a possible tool for establishing these connections. Applying this approach in the field of content-based image retrieval of art paintings provides a tool for extracting specific feature combinations, which represent different sides of artists' styles, periods and movements.