The invention provides a label system accurate recommendation method based on user comment analysis. The interest model is constructed according to the user-commodity-label ternary relation, the accurate recommendation method more suitable for the label system is obtained, and in view of the problems that label information data of users in the label system generally has data sparseness and the user similarity calculated by using sparse data is low in accuracy, user comment data is creatively introduced, text analysis on user comment information is carried out, Chinese word segmentation and keyword extraction on the comment information are carried out, the extracted keywords are taken as pseudo tags, user labels are extracted, the label information data is expanded, the problem of label information data sparseness is solved, meanwhile, based on the fact that user comment information contains user preferences, value assignment calculation is conducted on emotion words in the comment information, the score value of a user for a commodity is obtained from user comments, the obtained score value information is used for further improving a label algorithm, and the accuracy of a recommendation result is improved.