Open AccessAssessment of ontological structures semantic similarity based on a modified cuckoo search algorithm
Author(s) -
Yurii Kravchenko,
Victoria Bova
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/734/1/012018
Subject(s) - cuckoo search , similarity (geometry) , computer science , semantic similarity , process (computing) , cuckoo , quality (philosophy) , nesting (process) , algorithm , artificial intelligence , theoretical computer science , zoology , philosophy , materials science , epistemology , particle swarm optimization , metallurgy , image (mathematics) , biology , operating system
Enhancing the effectiveness of knowledge (information) classification and integration based on an assessment of semantic similarity of ontological structures is an urgent scientific problem. Evaluation of equivalent semantic similarity requires considerable computational resources. Consequently, a similarity of predicates of all ontologies’ concepts shall be verified in the exhaustive search. Exact methods do not allow to find a solution in polynomial time, since this problem is trans-computational and requires the use of random search approaches with decentralized control. The paper proposed a modification of the algorithm, inspired by the behavior of cuckoos in the process of nesting parasitism. The cuckoo search optimization algorithm increases the stochasticity of obtained quasi-optimal solutions in comparison with other bioinspired algorithms and increase the search speed. A comparative analysis of the results quality showed that solutions, obtained by the cuckoos’ search, outperform the results of other bioinspired approaches.