Glancing at the problems of contemporary ontology
DOI:
https://doi.org/10.54886/scire.v8i1.1157Abstract
Ontology is the talk of the day in various chapters of AI (NLP, IR, DB modeling among others). Ontology comes into play as a viable strategy with which, for example, to construct robust domain models. An ontologically grounded knowledge of the objects of a domain should make their codification simpler, more transparent and more natural. Indeed, ontology can give greater robustness to models by furnishing criteria and categories with which to organize and construct them; and it is also able to provide contexts in which different models can be embedded and recategorized to acquire greater reciprocal transparency. The recent interest in ontology exhibited by AI scholars will be analyzed and the main ongoing projects will be shortly discussed. The difference between ontology as technology and ontology as conceptual analysis (that is, the difference between ontology as understood by mainstream AI scholars and ontology as understood by philosophers) will be presented as wellDownloads
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
© 1996- . Authors retain their copyright, but transfer the exploitation rights (reproduction, distribution, public communication and transformation) to the journal in a non-exclusive way and guarantee the right to the first publication of their work to the journal, which will be simultaneously subjected to the license CC BY-NC-ND. Authors take whole personal responsibility on fulfilling all the appropiate ethical codes and laws, and obtaining all the necessary copyright permissions regarding their articles. Institutional and self- archiving is allowed and encouraged.
