Should Terminology Principles be re-examined?
September 16, 2016 Β· Declared Dead Β· π Terminology and Knowledge Engineering
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Christophe Roche
arXiv ID
1609.05170
Category
cs.AI: Artificial Intelligence
Citations
13
Venue
Terminology and Knowledge Engineering
Last Checked
4 months ago
Abstract
Operationalization of terminology for IT applications has revived the Wusterian approach. The conceptual dimension once more prevails after taking back seat to specialised lexicography. This is demonstrated by the emergence of ontology in terminology. While the Terminology Principles as defined in Felber manual and the ISO standards remain at the core of traditional terminology, their computational implementation raises some issues. In this article, while reiterating their importance, we will be re-examining these Principles from a dual perspective: that of logic in the mathematical sense of the term and that of epistemology as in the theory of knowledge. We will thus be clarifying and describing some of them so as to take into account advances in knowledge engineering (ontology) and formal systems (logic). The notion of ontoterminology, terminology whose conceptual system is a formal ontology, results from this approach.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Artificial Intelligence
π
π
The Cartographer
R.I.P.
π»
Ghosted
Explanation in Artificial Intelligence: Insights from the Social Sciences
R.I.P.
π»
Ghosted
Federated Machine Learning: Concept and Applications
R.I.P.
π»
Ghosted
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
R.I.P.
π»
Ghosted
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
R.I.P.
π»
Ghosted
Rainbow: Combining Improvements in Deep Reinforcement Learning
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted