The doctoral thesis describes results of the research on integration of knowledge cartography techniques and intelligent concept map-based knowledge assessment system. The thesis contains theoretical research in concept maps, their diversity, diversity in concept map-based tasks, software supporting concept mapping and how it affects work load of a teachers as well as indication of directions in intelligent concept map-based knowledge assessment system development. Study of knowledge cartography techniques is done and it is concluded that ontology is the most appropriate for integration with intelligent concept map-based knowledge assessment system IKAS. Analysis of definitions and classification schemas of ontologies and their systematisation is accomplished. Algorithms improving operation of the intelligent concept map-based knowledge assessment system IKAS are developed. Two algorithms perform concept map transformation into ontologies and ontology transformation into concept maps. Besides algorithms for extending the functionality of intelligent concept map-based knowledge assessment system as a system for knowledge self-assessment, i.e., algorithms for compiling learning paths for a whole study course and a personalised learning path for the particular learner are also developed. The algorithms are implemented in OntoKJ and JKOnto tools and they are tested using hardware ontology and concept maps for study courses in artificial intelligence.