Patent ID: 9134957
Filing Date: 2015-09-15
Classification: G06F

Abstract:
1. A method of recommending tags for user, the method comprising: receiving, with a processing device, a current rating of a current user on current objects; determining a candidate tag set based on the current user and the current rating by determining history tags of the current user under the current rating as the candidate tag set based on a predetermined correlative relationship of the user with history tags under different rating levels, wherein the correlative relationship of the user with content of history tags under different rating levels comprises similarity between each two of the objects, which is determined based on content similarity of history tags of the objects and rating similarity of different users on a same object; wherein each object has a first vector and a second vector, the first vector is term frequency/inverse document frequency value of that object on corresponding history tags, and the second vector is history rating on that object, and determination of the similarity between each two of the objects comprises: determining the content similarity Sim1(i, j) based on similarity between the first vectors; determining the rating similarity Sim2(i, j) based on similarity between the second vectors; and determining the similarity between each two of the objects Sim(i, j)=Sim1(i, j)*a+Sim2(i, j)*(1−a), wherein 0<a<1, parameter a is used for adjusting weight; ordering candidate tags in the candidate tag set based on index values thereof; and recommending tags for the current user based on the ordering of the candidate tags in the candidate tag set.