Social Tag Recommendation Based on Weighted Tuples Latent Semantic Analysis
In the social tagging system, user generated tags is random and weak relevance, this will leadto reduced accuracy in tag recommendation. In this paper, based on weighted tuples latent semantic struc ture model of three dimensional tensor, introduction of social network structured analysis method to quan tify and weight the related tuples, to construct weighted structure model of three dimensional tensor, andthrough the latent semantic analysis of tuples, get weighted tuples sets that can reflect the measure of userinterest. Finally, Through the user marking data set of the typical Delicious websites, verified based onweighted tuples latent semantic analysis model of three dimensional tensor has better effect of tag recom mendation.