Abstract
This research employs Description Logics in order to focus on logical description and analysis of the phenomenon of ‘concept understanding’. The article will deal with a formal-semantic model for figuring out the underlying logical assumptions of ‘concept understanding’ in knowledge representation systems. In other words, it attempts to describe a theoretical model for concept understanding and to reflect the phenomenon of ‘concept understanding’ in terminological knowledge representation systems. Finally, it will design an ontology that schemes the structure of concept understanding based on the proposed semantic model.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
For brevity, I use ‘he’ and ‘his’ whenever ‘he or she’ and ‘his or her’ are meant.
References
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P.: The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, New York (2010)
Badie, F.: Concept representation analysis in the context of human-machine interactions. In: Proceedings of the 14th International Conference on e-Society. International Association for Development of the Information Society, Portugal (2016a)
Badie, F.: Towards concept understanding relying on conceptualisation in constructivist learning. In: Proceedings of the 13th International Conference on Cognition and Exploratory Learning in Digital Age. International Association for Development of the Information Society, Germany (2016b)
Badie, F.: A formal semantics for concept understanding relying on description logics. In: Proceedings of the 9th International Conference on Agents and Artificial Intelligence. SCITEPRESS Digital Library, Portugal (2017)
Barsalou, L.W.: Perceptual Symbol Systems. The Behavioural and Brain Sciences. Cambridge University Press, New York (1999)
Biggs, J.B., Collis, K.F.: Evaluating the Quality of Learning: The SOLO Taxonomy (Structure of the Observed Learning Outcome). Academic Press, New York (2014)
Blackburn, S.: The Oxford Dictionary of Philosophy. Oxford University Press, Oxford (2016). Web
Chaitin, G.J.: Algorithmic Information Theory. Cambridge University Press, New York (1987)
Davies, J., Fensel, D., van Harmelen, F.: Towards the Semantic Web, Ontology-Driven Knowledge Management. Wiley Online Publications, New York (2003)
di Pellegrino, G., Fadiga, L., Fogassi, L., Gallese, V., Rizzolatti, G.: Understanding motor events: a neurophysiological study. Exp. Brain Res. 91, 176–180 (1992)
von Foerster, H.: Understanding Understanding, Essays on Cybernetics and Cognition. Springer, New York (2003)
Gray, P.M.D., Kulkarni, K.G., Paton, N.W.: Object-Oriented Databases - A Semantic Data Model Approach. Prentice Hall International Series in Computer Science. Prentice Hall, London (1992)
Stephan, G., Pascal, H., Andreas, A.: Knowledge representation and ontologies. In: Studer, R., Grimm, S., Abecker, A. (eds.) Semantic Web Services, pp. 51–105. Springer, Heidelberg (2007). https://doi.org/10.1007/3-540-70894-4_3
Honderich, T.: The Oxford Companion to Philosophy. Oxford University Press, Oxford (2005)
Jackendoff, R.: Semantic Structures. MIT Press, Cambridge (1990)
Kant, I.: Kritik der reinen Vernunft. VMA-Verlag, Wiesbaden. (imprint of the 1924 edt.), p. 967 et passim (1781)
Kintsch, W., Welsch, D., Schmalhofer, F., Zimny, S.: Sentence memory: a theoretical analysis. J. Mem. Lang. 29, 133–159 (1990). Elsevier
MacKay, D.: Information Theory, Inference and Learning Algorithms. Cambridge University Press, New York (2003)
Peschl, M.F., Riegler, A.: Does representation need reality? Rethinking Epistemological issues in the light of recent developments and concepts in cognitive science. In: Riegler, A., Peschl, M., von Stein, A. (eds.) Understanding Representation in the Cognitive Sciences, pp. 9–17. Springer, Boston (1999). https://doi.org/10.1007/978-0-585-29605-0_1
Resnik, P.: Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. J. Artif. Intell. Res. 11, 95–130 (1999)
Schmidt-Schauss, M., Smolka, G.: Attributive concept descriptions with complements. Artif. Intell. 48(1), 1–26 (1991). Elsevier
Simpson, J.A., Weiner, E.S.C.: The Oxford English Dictionary. Oxford University Press, Oxford (1989)
Staab, S., Studer, R.: Handbook on Ontologies, 2nd edn. Springer, Heidelberg (2009)
Uithol, S., van Rooij, I., Bekkering, H., Haselager, P.: Understanding motor resonance. J. Soc. Neurosci. 6(4), 388–397 (2011). Routledge
Uithol, S., Paulus, M.: What do infants understand of others’ action? A theoretical account of early social cognition. Psychol. Res. 78(5), 609–622 (2014)
Webb, J.: Understanding Representation. Sage Publications, London (2009)
Zwaan, R.A., Taylor, L.J.: Seeing, acting, understanding: motor resonance in language comprehension. J. Exp. Psychol. Gen. 135(1), 1–11 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Badie, F. (2018). A Description Logic Based Knowledge Representation Model for Concept Understanding. In: van den Herik, J., Rocha, A., Filipe, J. (eds) Agents and Artificial Intelligence. ICAART 2017. Lecture Notes in Computer Science(), vol 10839. Springer, Cham. https://doi.org/10.1007/978-3-319-93581-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-93581-2_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-93580-5
Online ISBN: 978-3-319-93581-2
eBook Packages: Computer ScienceComputer Science (R0)