Creating statistics from sporting events is now widespread with most efforts to automate this process using various sensor devices. The problem with many of these statistical app...
Some supervised-learning algorithms can make effective use of domain knowledge in addition to the input-output pairs commonly used in machine learning. However, formulating this a...
The aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. The pr...
In this paper, we show how a domain dependent know-how textual database of advices and warnings can be constructed from procedural texts. We show how arguments of type warnings an...
Abstract. The definition of a domain ontology is a complex activity that requires two kinds of expertise: a deep knowledge of the domain to be modeled and a good level of familiari...