作者: Fabian M. Suchanek , Serge Abiteboul , Pierre Senellart
关键词: Computer science 、 Probabilistic logic 、 Schema (psychology) 、 Ontology (information science) 、 Semantic Web 、 Theoretical computer science 、 Data mining 、 Ontology alignment
摘要: One of the main challenges that Semantic Web faces is integration a growing number independently designed ontologies. In this work, we present paris, an approach for automatic alignment paris aligns not only instances, but also relations and classes. Alignments at instance level cross-fertilize with alignments schema level. Thereby, our system provides truly holistic solution to problem ontology alignment. The heart probabilistic, i.e., measure degrees matchings based on probability estimates. This allows run without any parameter tuning. We demonstrate efficiency algorithm its precision through extensive experiments. particular, obtain around 90% in experiments some world's largest