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The sharing and interoperation of geographical information has always been a hot topic in the field of geographical information science, and the semantic similarity of the concept of geographic information is also an important factor affecting geographic information sharing and interoperability. The semantic similarity of concept calculation is a natural language processing, an important component of the study, but also applications of artificial intelligence problems to be solved. Ontology, which is an explicit and formal specification of sharing information, becoming an effective method for solve the problem of semantic similarity. Considering the special nature of the concept of geographic information, this paper takes an integrated multi-point semantic similarity calculation method in this paper. We made an investigation on the distance-based semantic similarity calculation model, the attribute-based semantic similarity calculation model, the relationship between concepts-based semantic similarity calculation models. And we analyzed all aspects of the concept of geographic information. Then, considering the impact of the distance, the attributes, the relationship between concepts for the semantic similarity of the concept of geographic information, this paper established an integrated and multi-angle model for the semantic similarity calculation of geographic information concept. And we added some adjustable parameters to adapt the flexible application. Make sure the calculation results more accurate and objective. By precise experimental analysis, this integrated model can improve the calculation accuracy.