ILP systems induce rst-order clausal theories performing asearch through very large hypotheses spaces containing redundant hypotheses.The generation of redundant hypotheses may prevent the systemsfrom nding good models and increases the time to induce them.In this paper we propose a classication of hypotheses redundancy andshow how expert knowledge can be provided to an ILP system to avoidit. Experimental results show that the number of hypotheses generatedand execution time are reduced when expert knowledge is used to avoidredundancy
The hypotheses constructed by Inductive Logic Programming (ILP) systems are logic programs that comp...
AbstractThe inductive synthesis of recursive logic programs from incomplete information, such as inp...
Inductive reasoning is a core problem-solving capacity: humans can identify underlying principles fr...
Abstract. ILP systems induce first-order clausal theories performing a search through very large hyp...
Inductive Logic Programming (ILP) systems apply inductive learning to an inductive learning task by ...
We developed and implemented an inductive logic programming system and the first order classifier, c...
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises trainin...
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises trainin...
Inductive Logic Programming (ILP) is a powerful and welldeveloped abstraction for multi-relational d...
Inductive Logic Programming (ILP) is a promising technology for knowledgeextraction applications. IL...
Significant research has been conducted in recent years to extend Inductive Logic Programming (ILP) ...
We propose and evaluate a technique to improve the eciency of an ILP system. The technique avoids th...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
Inductive Logic Programming (ILP) is a promising technol-ogy for knowledge extraction applications. ...
International audienceHandling redundancy in propositional reasoning and search is an active path of...
The hypotheses constructed by Inductive Logic Programming (ILP) systems are logic programs that comp...
AbstractThe inductive synthesis of recursive logic programs from incomplete information, such as inp...
Inductive reasoning is a core problem-solving capacity: humans can identify underlying principles fr...
Abstract. ILP systems induce first-order clausal theories performing a search through very large hyp...
Inductive Logic Programming (ILP) systems apply inductive learning to an inductive learning task by ...
We developed and implemented an inductive logic programming system and the first order classifier, c...
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises trainin...
The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises trainin...
Inductive Logic Programming (ILP) is a powerful and welldeveloped abstraction for multi-relational d...
Inductive Logic Programming (ILP) is a promising technology for knowledgeextraction applications. IL...
Significant research has been conducted in recent years to extend Inductive Logic Programming (ILP) ...
We propose and evaluate a technique to improve the eciency of an ILP system. The technique avoids th...
Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction ...
Inductive Logic Programming (ILP) is a promising technol-ogy for knowledge extraction applications. ...
International audienceHandling redundancy in propositional reasoning and search is an active path of...
The hypotheses constructed by Inductive Logic Programming (ILP) systems are logic programs that comp...
AbstractThe inductive synthesis of recursive logic programs from incomplete information, such as inp...
Inductive reasoning is a core problem-solving capacity: humans can identify underlying principles fr...