Radar intelligence distribution on demand based on content similarity forms user information recommendation by computing the similarity. But the traditional similarity algorithms assume that all characteristics have the same importance, which conflicts with known facts. To this end, a content similarity calculation method based on feature weighting is proposed. The method considers the different influence on the results by various dimensional characteristics, uses ReliefF algorithm to give the feature weights, selects features according to the characteristics of the importance, and forms the nearest neighbor area based on weighted content similarity through calculating the content of the similarity. On this basis, the recommendation of new information to the user is predicted, the radar intelligence distribution on demand according to the degree of interest is realized. The simulation results show that the algorithm has better performance and better prediction effect than the traditional content similarity recommendation method.