Personalized resource recommendation in CTS using graph-based clustering
Bo Lin · Computer Engineering and Applications Journal · 2010
The flexibility of Collaborative Tagging Systems(CTS) brings large number of synonymous and polysemous tags which make the use of these profile information to personalize resource recommendation difficult.Graph-based tag clustering is proposed to form groups of semantically-related tags.Then the tag clusters act as an intermediary between users and resource and are utilized to personalize the query results in CTS.5-fold cross-validation is performed on two data sets,and the results are compared with two other algorithms.Results show that the proposed algorithm demonstrate much better personalization measured by the Fvalue,and the effect is more miraculous in a multi-topic than in a single-topic CTS.This observation suggests that in a multitopic CTS tag clustering such as proposed in this paper is an important strategy.