Geography Ontology Fusion Model Based on Statistical Machine Learning

Abstract:

The ubiquity of geography ontology heterogeneity is caused by multiple cognitive systems for geographical object.Geography ontology fusion model was proposed by introducing the method of automatic statistical machine learning for processing relationship within the concepts.The credibility was produced according to emergence frequency of relationship between concepts in different ontology and finally a large-scale integrated geographic concept space with statistic and field information was generated.Cumbersome concept mapping process is circumvented through this model,and all the knowledge expressed in ontologies is fused while information within each field is preserved in this concept space which realize sharing between multiple cognitive systems.