Tag recommendation based on topic hierarchy of folksonomy

Abstract

As a recommendation problem, tag recommendation has been receiving increasing attention from both the business and academic communities. Traditional recommendation methods are inappropriate for folksonomy because the basis of such mechanism remains un-updated in time owing to the bottleneck of knowledge acquisition. Therefore, we propose a novel method of tag recommendation based on the topic hierarchy of folksonomy. The method applies the topic tag hierarchy constructed automatically from folksonomy to tag recommendation using the proposed strategy. The method can improve the quality of folksonomy and can evaluate the topic tag hierarchy through tag recommendation. The precision of tag recommendation reaches 0.892. The experimental results show that the proposed method significantly outperforms state-of-the-art methods (t-test, p-value < 0.0001) and demonstrates effectiveness with respect to data sources on tag recommendation.