Skip to main content
SpringerLink
Log in

Evaluation of Digital Competence Profiles Using Dialetheic Logic

  • Article
  • Published:
International Journal of Artificial Intelligence in Education Aims and scope Submit manuscript

Abstract

Professional profiles are unstructured documents where the knowledge and experience of the editor predominate, presenting inconsistencies and ambiguities in terms of the competencies they contain, making complicated the recognition of knowledge and skills necessary for the proposal of university study programs. Also, the identification of knowledge and skills in digital academic profiles present difficulties due to their inconsistencies. This work proposes analyzing the contradictions or ambivalences found in the academic and professional competencies published in digital media (for example, web pages or social networks) through a model of axioms based on dialetheic logic. Notably, the model considers five types of natural language phenomena: Vagueness or ambiguity, presupposition failure, counterfactual reasoning, fictional discourse, and contingent statements about the future. In addition, the model uses lexical and semantic similarity measures in its analysis process. The dialetheic model is validated using several performance measures to determine its capability to find ambiguity in a competence ontology described using description logic. The results show that dialetheic logic is required to accurately interpret digital academic and professional profiles using computational reasoning mechanisms. The model applies in a Spanish context for computer science jobs, with the possibility to apply in other languages or domains, such as English, French, etc. Our model is a contribution for competencies management, which is useful for the automatic curriculum design, competencies validation in learning processes, among other uses.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. CONLL format, where NC: noun, SP; preposition and AQ: adjective.

References

  • Aguilar, J. (2011). Temporal Logic from the Chronicles Paradigm: learning and reasoning problems, and its applications in Distributed Systems. LAP Lambert Academic Publishing

  • Aguilar, J., Cordero, J., & Buendía, O. (2018). Specification of the autonomic cycles of learning analytic tasks for a smart classroom. Journal of Educational Computing Research, 56(6), 866–891

    Article  Google Scholar 

  • Aguilar, J., Jerez, M., & Rodríguez, T. (2018). CAMeOnto: Context awareness meta ontology modeling. Applied Computing and Informatics, 14(2), 202–213

    Article  Google Scholar 

  • Arruda, A. (1980). A survey of paraconsistent logic. Studies in logic and the foundations of mathematics 99, 1–41. https://doi.org/10.1016/S0049-237X(09)70477-X

  • Beaver, D. I. (1997). Presupposition. Handbook of logic and language (pp. 939–1008). North-Holland

  • Bourahla, M. (2015). Reasoning over vague concepts. Lecture Notes in Computer Science, 9120, 591-602

  • De Leenheer, P., De Moor, A., & Meersman, R. (2007). Context dependency management in ontology engineering: a formal approach. Lecture Notes in Computer Science, 4380, 26-56

  • Dorn, J., & Pichlmair, M. (2007). A Competence Management System for Universities. In European Conference on Information Systems (pp. 759-770)

  • Dubois, D., & Prade, H. (2012). Possibility theory: an approach to computerized processing of uncertainty. Springer Science & Business Media

  • Elchamaa, R., Mbaya, A., Moalla, N., Ouzrout, Y., & Bouras, A. (2019). Ontology for Continuous Learning and Support. Enterprise Interoperability VIII (pp. 191–202). Springer

  • Eklund, M. (2017). Fictionalism. The Stanford Encyclopedia of Philosophy. (E. Zalta). Stanford University

  • Faes, M. G., & Moens, D. (2019). Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty. Archives of Computational Methods in Engineering, 27, 633–671. https://doi.org/10.1007/s11831-019-09327-x.

    Article  MathSciNet  Google Scholar 

  • Fazel-Zarandi, M., & Fox, M. S. (2010). Reasoning about skills and competencies. In  L. M. Camarinha-Matos, X. Boucher, H. Afsarmanesh (Eds.), Collaborative Networks for a Sustainable World (336, pp. 372-379)

  • Gil-Vallejo, L., Castellón, I., & Coll-Florit, M. (2018). Similitud verbal: Análisis comparativo entre lingüística teórica y datos extraídos de corpus. Revista Signos, 51(98), 310–332

    Article  Google Scholar 

  • González-Eras, A. G., & Aguilar, J. (2015). Semantic architecture for the analysis of the academic and occupational profiles based on competencies. Contemporary Engineering Sciences, 8, 1551–1563

    Article  Google Scholar 

  • González-Eras, A., Buendia, O., Aguilar, J., Cordero, J., & Rodriguez, T. (2017). Competences as services in the autonomic cycles of learning analytic tasks for a smart classroom. In International Conference on Technologies and Innovation (pp. 211-226). Springer

  • González-Eras, A., & Aguilar, J. (2018). Esquema para la actualización de Ontologías de Competencias en base al Procesamiento del Lenguaje Natural y la Minería Semántica (pp. 433–447). Revista Ibérica de Sistemas e Tecnologias de InformaçãoE17

  • González-Eras, A., & Aguilar, J. (2019). Determination of professional competencies using an alignment algorithm of academic and professional profiles, based on competence thesauri and similarity measures. International Journal of Artificial Intelligence in Education, 29(4), 536–567

    Article  Google Scholar 

  • Gluga, R., Kay, J., & Lever, T. (2013). Foundations for modeling university curricula in terms of multiple learning goal sets. IEEE Transactions on Learning Technologies, 6(1), 25–37

    Article  Google Scholar 

  • Guevara, C., Aguilar, J., & González-Eras, A. (2017). The model of adaptive learning objects for virtual environments instanced by the competencies. Advances in Science, Technology and Engineering Systems Journal, 2(3), 345–355

    Article  Google Scholar 

  • Guo, S., Alamudun, F., & Hammond, T. (2016). RésuMatcher: A personalized résumé-job matching system. Expert Systems with Applications, 60, 169–182

    Article  Google Scholar 

  • Gutiérrez-Basulto, V., Jung, J. C., Lutz, C., & Schröder, L. (2017). Probabilistic description logics for subjective uncertainty. Journal of Artificial Intelligence Research, 58, 1–66

    Article  MathSciNet  MATH  Google Scholar 

  • Hassan, F. M., Ghani, I., Faheem, M., & Hajji, A. A. (2012). Ontology matching approaches for eRecruitment. International Journal of Computer Applications, 51(2), 39–45

    Article  Google Scholar 

  • Haque, E., & Chiang, F. (2019). Restoring consistency in ontological multidimensional data models via weighted repairs. Procedia Computer Science, 159, 1085–1094

    Article  Google Scholar 

  • Horrocks, I., Patel-Schneider, P. F., & Van Harmelen, F. (2003). From SHIQ and RDF to OWL: The making of a web ontology language. Journal of Web Semantics, 1(1), 7–26

    Article  Google Scholar 

  • Janev, V., & Vranes, S. (2011). Ontology-based competency management: the case study of the Mihajlo Pupin Institute. Journal of Universal Computer Science, 17(7), 1089–1108

    Google Scholar 

  • Jiménez, C., Jerez, M., Aguilar, J., & García, R. (2019). Linked data and dialetheic logic for localization-aware applications. Contemporary Engineering Sciences, 12(3), 103–116

    Article  Google Scholar 

  • Kravcik, M., Wang, X., Ullrich, C., & Igel, C. (2018). Towards competence development for industry 4.0. In International Conference on Artificial Intelligence in Education (pp. 442-446). Springer

  • Kondratova, I., Molyneaux, H., & Fournier, H. (2017). Design considerations for competency functionality within a learning ecosystem. In International Conference on Learning and Collaboration Technologies (pp. 124-136). Springer

  • Lukasiewicz, T., & Straccia, U. (2008). Managing uncertainty and Vagueness in description logics for the semantic web. Journal of Web Semantics, 6(4), 291–308

    Article  Google Scholar 

  • Malzahn, N., Ziebarth, S., & Hoppe, H. U. (2013). Semi-automatic creation and exploitation of competence ontologies for trend aware profiling, matching and planning. Knowledge Management & E-Learning: An International Journal, 5(1), 84-103

  • Mendonça, M., Perozo, N., & Aguilar, J. (2015). An approach for Multiple Combination of Ontologies based on the Ants Colony Optimization Algorithm. In Asia-Pacific Conference on Computer-Aided System Engineering (APCASE), (pp. 140-145)

  • Mendonça, M., Perozo, N., & Aguilar, J. (2020). Ontological emergence scheme in self-organized and emerging systems. Advanced Engineering Informatics, 44, 101045

    Article  Google Scholar 

  • Menzies, P. (2001). Counterfactual theories of causation. Stanford Encyclopedia of Philosophy (E. Zalta), Stanford University

  • Miranda, S., Orciuoli, F., Loia, V., & Sampson, D. (2017). An ontology-based model for competence management. Data & Knowledge Engineering, 107, 51–66

    Article  Google Scholar 

  • Montuschi, P., Lamberti, F., Gatteschi, V., & Demartini, C. (2015). A semantic recommender system for adaptive learning. IT Professional, 5, 50–58

    Article  Google Scholar 

  • Paquette, G., Rogozan, D., & Marino, O. (2012). Competency comparison relations for recommendation in technology enhanced learning scenarios. In RecSysTEL 2012 Proceedings (pp. 23-34)

  • Perozo, N., Aguilar, J., Terán, O., & Molina, H. (2013). A Verification Method for MASOES. IEEE Transactions on Cybernetics, 43(1), 64–76

    Article  Google Scholar 

  • Pelletier, F. J., Sutcliffe, G., & Hazen, A. P. (2017). Automated reasoning for the dialetheic logic RM3. In 30th International Florida Artificial Intelligence Research Society Conference (pp. 110-115)

  • Peter, O., & Hasle, P. (2015). Future Contingents. Stanford Encyclopedia of Philosophy. (E. Zalta), Stanford University

  • Pulcini, G., & Varzi, A. C. (2018). Paraconsistency in classical logic. Synthese, 195(12), 5485–5496

    Article  MathSciNet  MATH  Google Scholar 

  • Puerto, E., Aguilar, J., & Rodriguez, T. (2012). Automatic learning of ontologies for the semantic web: experiment lexical learning. Revista Respuestas, 17(2), 5–12

    Article  Google Scholar 

  • Ramsauer, C. (2020). Competencies of production in SMEs in assembly industries in a digital volatile business environment. Tehnički Glasnik, 14(3), 388–395

    Article  Google Scholar 

  • Robertson, S., & Zaragoza, H. (2009). The probabilistic relevance framework: BM25 and beyond. Now Publishers Inc

  • Rodriguez, T., Puerto, E., & Aguilar, J. (2010). Dynamic semantics ontological framework for web semantics. In 9th WSEAS Intl. Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (pp. 91-98)

  • Sateli, B., Löffler, F., König-Ries, B., & Witte, R. (2017). ScholarLens: extracting competences from research publications for the automatic generation of semantic user profiles. PeerJ Computer Science, 3, e121

  • Sikos, L. F. (2017). Description Logics in Multimedia Reasoning. Springer International Publishing

  • Sorensen, R. (2018). Vagueness. Stanford Encyclopedia of Philosophy (E. Zalta). Stanford University

  • Sutcliffe, G., Schulz, S., Claessen, K., & Baumgartner, P. (2012). The TPTP typed first-order form with arithmetic. Lecture Notes in Computer Science, 7180, 406-419

  • Sutcliffe, G., & Pelletier, F. (2019). JGXYZ: An ATP system for gap and glut logics. Lecture Notes in Computer Science, 11716, 526-537

  • Zamansky, A. (2019). On recent applications of paraconsistent logic: an exploratory literature review. Journal of Applied Non-Classical Logics, 29(4), 382–391

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departamento de Ciencias de la Computación y Electrónica, Universidad Técnica Particular de Loja, Cdla. Universitaria San Cayetano Alto, 1101608, Loja, Ecuador

    Alexandra González-Eras

  2. Centro de Estudios en Microelectrónica y Sistemas Distribuidos, Facultad de Ingeniería, Universidad de Los Andes, 5101, Mérida, Venezuela

    Alexandra González-Eras, Ricardo Dos Santos & Jose Aguilar

  3. Tepuy R+D Group. Artificial Intelligence Software Development, Mérida, Venezuela

    Alexandra González-Eras, Ricardo Dos Santos & Jose Aguilar

  4. GIDITIC, Escuela de Ingeniería, Universidad EAFIT, Medellín, Colombia

    Jose Aguilar

  5. Departamento de Automática, Universidad de Alcalá, Alcalá de Henares, Spain

    Jose Aguilar

Authors
  1. Alexandra González-Eras
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ricardo Dos Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jose Aguilar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jose Aguilar.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

González-Eras, A., Dos Santos, R. & Aguilar, J. Evaluation of Digital Competence Profiles Using Dialetheic Logic. Int J Artif Intell Educ 33, 59–87 (2023). https://doi.org/10.1007/s40593-021-00286-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40593-021-00286-8

Keywords

Search

Navigation