An ontology selection and ranking system based on the analytic hierarchy process
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GROZA, Adrian, DRAGOSTE, Irina, SINCAI, Iulia, JIMBOREAN, Ioana, MORARU, Vasile. An ontology selection and ranking system based on the analytic hierarchy process. In: Symposium on Symbolic and Numeric Algorithms for Scientific Computing: SYNASC 2014, Ed. 16, 22-25 septembrie 2014, Timișoara. New Jersey, SUA: Institute of Electrical and Electronics Engineers Inc., 2015, Ediția 16, pp. 293-300. ISBN 978-147998448-0. DOI: https://doi.org/10.1109/SYNASC.2014.47
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Symposium on Symbolic and Numeric Algorithms for Scientific Computing
Ediția 16, 2015
Simpozionul "16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing"
16, Timișoara, Romania, 22-25 septembrie 2014

An ontology selection and ranking system based on the analytic hierarchy process

DOI:https://doi.org/10.1109/SYNASC.2014.47

Pag. 293-300

Groza Adrian1, Dragoste Irina1, Sincai Iulia1, Jimborean Ioana1, Moraru Vasile2
 
1 Technical University of Cluj-Napoca,
2 Technical University of Moldova
 
 
Disponibil în IBN: 20 aprilie 2023


Rezumat

Selecting the desired ontology from a collection of available ones is essential for ontology reuse. We address the problem of evaluating, ranking and selecting ontologies according to user preferences. We exploit the Analytic Hierarchy Process (AHP) to solve the multiple-criteria decision problem and to model the preferences of the users. We use AHP to analyze the available ontologies from different perspectives and at different abstraction levels. The decision is based on the concrete end-node measurements and their relative importance at higher levels. For supporting the selection decision, we developed an ontology representation, reasoning and management system. The system applies different metrics on ontologies in order to feed the Analytic Hierarchy Process with facts. The running scenario applies our method to the task of reusing ontologies from the tourism domain. 

Cuvinte-cheie
analytic hierarchy process, ontology metrics, ontology ranking, Ontology selection