Learning to Map Ontologies with Neural Network

In this paper the authors applied the idea of training multiple tasks simultaneously on a partially shared feed forward network to domain of ontology mapping. A “cross training” mechanism was used to specify corresponding nodes between the two ontologies. By examining output of one network in response to stimulus from the other network, we can test if the network can learn the correspondence that was not cross-trained. Two kinds of studies on ontology mapping were conducted. The result shows the network can fill in the missing mappings between ontologies with sufficient training data.