Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Logic programming and databases
Logic programming and databases
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
A Generalization Model Based on OI-implication for Ideal Theory Refinement
Fundamenta Informaticae - Intelligent Systems
A General Similarity Framework for Horn Clause Logic
Fundamenta Informaticae
Unsupervised discretization using kernel density estimation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Plugging Taxonomic Similarity in First-Order Logic Horn Clauses Comparison
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
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Horn clause Logic is a powerful representation language exploited in Logic Programming as a computer programming framework and in Inductive Logic Programming as a formalism for expressing examples and learned theories in domains where relations among objects must be expressed to fully capture the relevant information. While the predicates that make up the description language are defined by the knowledge engineer and handled only syntactically by the interpreters, they sometimes express information that can be properly exploited only with reference to a suitable background knowledge in order to capture unexpressed and underlying relationships among the concepts described. This is typical when the representation includes numerical information, such as single values or intervals, for which simple syntactic matching is not sufficient. This work proposes an extension of an existing framework for similarity assessment between First-Order Logic Horn clauses, that is able to handle numeric information in the descriptions. The viability of the solution is demonstrated on sample problems.