In ontology mapping based on similarity calculation, the main reason for the large amount of similarity calculation is that there are too many concepts to be mapped and attributes to be calculated. This paper adopts a filtering strategy, using candidate mapping strategy and information gain strategy to reduce the number of concepts to be mapped and attributes to be calculated. This filtering strategy makes full use of the characteristics of ontology and data mining ideas, effectively filters out concepts and attributes that have no computational significance, and reduces the amount of similarity calculation. Experimental results show that the filtered concepts and attributes have little effect on the mapping effect. Keywords: ontology mapping; candidate mapping; information gain
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