4 papers
Predicting rice blast disease: machine learning versus process based models
David F. Nettleton, Dimitrios Katsantonis, Argyris Kalaitzidis +3
Rice is the second most important cereal crop worldwide, and the first in terms of number of people who depend on it as a major staple food. Rice blast disease is the most importan…
Trepan Reloaded: A Knowledge-driven Approach to Explaining Artificial Neural Networks
Roberto Confalonieri, Tillman Weyde, Tarek R. Besold +1
Explainability in Artificial Intelligence has been revived as a topic of active research by the need of conveying safety and trust to users in the `how' and `why' of automated deci…
Repairing Ontologies via Axiom Weakening
Nicolas Troquard, Roberto Confalonieri, Pietro Galliani +3
Ontology engineering is a hard and error-prone task, in which small changes may lead to errors, or even produce an inconsistent ontology. As ontologies grow in size, the need for a…
An Argument-based Creative Assistant for Harmonic Blending
Maximos Kaliakatsos-Papakostas, Roberto Confalonieri, Joseph Corneli +2
Conceptual blending is a powerful tool for computational creativity where, for example, the properties of two harmonic spaces may be combined in a consistent manner to produce a no…