The information provided by search engines lacks relevance and integrity, which is not conducive to the optimal travel route design. To solve such problem, a personalized tourism route recommendation strategy based on knowledge map is proposed. The scheme takes the personalized needs of users as input, and plans tourism routes according to the characteristics of the knowledge map in the tourism field. Then, through the integration of knowledge map and recommendation system, the recommendation performance is enhanced. The experimental analysis tests the rationality and effectiveness of personalized recommendation by using the representation route in the actual map. The experimental results based on real tourism big data show that it can consider multiple factors in personalized tourism, which is superior to similar algorithms in terms of hit rate and average reciprocal ranking.