Raffaele Cannone

Learn More
Computing with words (CWW) relies on linguistic representation of knowledge that is processed by operating at the semantical level defined through fuzzy sets. Linguistic representation of knowledge is a major issue when fuzzy rule based models are acquired from data by some form of empirical learning. Indeed, these models are often requested to exhibit(More)
When approaching real-world problems with intelligent systems, an interaction with user is often expected. However, data-driven models are usually evaluated only in terms of accuracy, thus not involving users. In literature several works have been proposed for defining measures for interpretability assessment, however, such measures are mostly based on a(More)
Interpretability represents the most important driving force behind the implementation of fuzzy logic-based systems. It can be directly related to the system’s knowledge base, with reference to the human user’s easiness experienced while reading and understanding the embedded pieces of information. In this paper, we present a preliminary(More)
  • 1