Method for Ontology Content and Structure Optimization, Provided by a Weighted Conceptual Graph

The complex dynamic structure of the ontology and its content requires implementing of optimization procedures to better ontology processing performance and resolve conflicts between data. This paper addresses the issues of ontology optimization with the purpose ofadapting its content to the needs of users by excluding those items that are rarely used or notused at all, or which do not belong or not related to a particular subject area. The approach isbased on automated weighting of concepts and relations during ontology learning. The ontology expanded in this way, is sequentially optimized according to criteria of integrity, absenceof ambiguity, volume, response time, completeness and thematic balance. The optimizationmethod of minimal spanning tree search was applied. This optimization task can be furtherreduced to the backpack problem for which the effective solving algorithms are known. Theuse of developed optimization techniques provides controlled automated ontology learning procedure that significantly expands the usability of ontology-based systems and reduces thetime expenditures on their implementation.