Induction of optimal semantic semi-distances for clausal knowledge bases
作者： Claudia d’Amato , Nicola Fanizzi , Floriana Esposito
DOI: 10.1007/978-3-540-78469-2_7
关键词: Computer science 、 Inductive reasoning 、 Similarity (psychology) 、 Artificial intelligence 、 Knowledge base 、 Natural language processing 、 Cluster analysis 、 Inductive logic programming 、 Markov logic network 、 Concept drift 、 Set (abstract data type)
摘要: Several activities related to semantically annotated resources can be enabled by a notion of similarity, spanning from clustering retrieval, matchmaking and other forms inductive reasoning. We propose the definition family semi-distances over set objects in knowledge base which used these activities. In line works on distance-induction clausal spaces, is parameterized committee concepts expressed with clauses. Hence, we also present method based idea simulated annealing optimize choice best concept committee.
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