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.