Application of category theory in the generation of meta-ontologies

Application of category theory in the generation of meta-ontologies

Maribel Mendonça Jose Aguilar  Niriaska Perozo 

Universidad Centroccidental Lisandro Alvarado, Lara, Venezuela

Universidad de Los Andes, Mérida, Venezuela Premeteo Researcher at the Escuela Politécnica Nacional, Quito and Universidad Técnica Particular de Loja, Ecuador

Corresponding Author Email: 
(mmendonca; nperozo) @ucla.edu.ve; aguilar@ula.ve
Page: 
11-38
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DOI: 
https://doi.org/10.3166/ISI.23.2.11-38
Received: 
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Accepted: 
| | Citation
Abstract: 

Meta-ontologies can be used to define a generic form of meta-concepts, which can be used for the modeling of ontologies and the ontological integration processes also. When there are several ontologies of the same domain, it is possible, from a combination process, to obtain important inputs for the generation of meta-concepts. Moreover, category theory allows defining in a formal way, the structures and the set of data that have common properties. In this article, we apply the category theory, in particular, the definitions of categories and sub-categories, in the process of generating of meta-concepts, as a way for the formalization of the automatic construction of meta-ontologies. The category theory is applied together with a collective intelligence approach based on the Ant Colony Optimization algorithm, during the combination process of multiple ontologies, in order to automate the meta-ontology construction.

Keywords: 

meta-ontologies, meta-concepts, category theory, collective intelligence

1. Introduction
2. Theoretical Aspects
3. Our Proposal
4. Case Study
5. Conclusions and future work
Acknowledgment

This work has been partially funded by the project Nro. 001-DCT-2015 and 013-RCT-2015 from CDCHT, Universidad Centroccidental Lisandro Alvarado, Venezuela.

  References

Aguilar J. (2001). A General Ant Colony Model to solve Combinatorial Optimization Problems. Revista Colombiana de Computación, vol. 2, n° 1, p. 7-18.

Aguilar J. (2014). Introducción a los Sistemas Emergentes, Talleres Gráficos, Universidad de Los Andes.

Aliyu S., Junaidu S.B., Kana A. D. (2015). A Category Theoretic Model of RDF Ontology. International Journal of Web & Semantic Technology (IJWesT), vol. 6, n° 3, p. 41-52.

Altamiranda J., Aguilar J., Delamarche C. (2015). Ant Colony Optimization for Construction of Common Pattern of the Protein Motifs. Proceedings of the International Conference on Bioinformatics & Computational Biology, p. 43-49.

Asperti A., Longo G. (1991). Categories, types, and structures: an introduction to category theory for the working computer scientist. MIT Press.

Barr M., Wells C. (1998). Category Theory for Computing Science. Technical Report Department of Mathematics and Statistics, McGill University

Cho J., Han S., Kim H. (2006). Meta-ontology for automated information integration of parts libraries. Computer-Aided Design, vol. 38, n° 7, p. 713-725.

Bonabeau E., Dorigo M., Theraulaz G. (1999). Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press

Guarino N., Welty C. (2000). A formal ontology of properties. International Conference on Knowledge Engineering and Knowledge Management, 1937, p. 97-112.

Guizzardi G. (2007). On ontology, ontologies, conceptualizations, modeling languages, and (meta) models. Frontiers in artificial intelligence and applications, 155, 18.

Kokla M., Kavouras M. (2001). Fusion of top-level and geographical domain ontologies based on context formation and complementarity. International Journal of Geographical Information Science, p. 679-687.

Mascardi V., Locoro A., & Rosso P. (2010). Automatic ontology matching via upper ontologies: A systematic evaluation. IEEE Transactions on Knowledge and Data Engineering, vol. 22, n° 5, 609-623.

Mendonca M., Aguilar J., Perozo N. (2015). An approach for Multiple Combination of Ontologies based on the Ants Colony Optimization Algorithm. Proceeding of the Asia-Pacific Conference on Computer Aided System Engineering, p. 140-145.

Mendonca M., Aguilar J., Perozo N. (2016). MiR-EO: Reflective Middleware for Ontological Emergency in Intelligent Environments. Latin American Journal of Computing, vol. 3, n° 2, p. 25-39.

Milton S., Smith B. (2004). Top-level ontology: The problem with naturalism. In Formal ontology in information systems, p. 85-94.

Pinto H., Gómez-Pérez A., Martins J. (1999). Some issues on ontology integration. Proceeding of the 16th International Joint Conference on Artificial Intelligence, p. 7-12.

Ramos E., Nuñez H. (2007). Ontologías: componentes, metodologías, lenguajes, herramientas y aplicaciones. Lecturas en Ciencias de la Computación, p. 1-42.

Rangel C., Aguilar J., Cerrada M., Altamiranda J. (2015). An Approach for the Emerging Ontology Alignment based on the Bees Colonies. Proceedings of the International Conference on Artificial Intelligence, p. 536-541.

Spivak D. (2014). Category theory for the sciences. MIT Press.

Yudelson M., Gavrilova T., Brusilovsky P. (2005). Towards user modeling meta-ontology. Proceeding of the International Conference on User Modeling, p. 448-452.

Zimmermann A., Krötzsch, M., Euzenat J., Pascal, H. (2006). Formalizing ontology alignment and its operations with category theory. Proc. 4th International conference on Formal ontology in information systems, p. 277-288.