Autonomy Oriented Personalized Tag Recommendation
Daming Sun · Dianzi xuebao · 2012
In a social tagging system,a user's tagging habits,including choosing which resource to tag and using which tag to annotate a resource,are affected by one's own autonomy.Available personalized rag recommendation methods lack the ability to model such autonomy information,and limit the performance of these methods.This paper proposed a latent Dirichlet allocation like probabilistic approach,which modeled user autonomy information such as one's preferences on tag and resource use,to provide autonomy oriented personalized tag recommendations.The parameters of the proposed method were estimated following a Gibbs sampling approach,which allowed a quick calculation of the values.Experiment results showed that the proposed approach can provide personalized tag recommendations with higher quality.