Folksonomy-Based Tag Recommendation for Collaborative Tagging Systems

Frederic Font, Joan Serrà and Xavier Serra
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Frederic Font: Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain
Joan Serrà: Artificial Intelligence Research Institute (IIIA-CSIC), Spanish National Research Council, Bellaterra, Spain
Xavier Serra: Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain

International Journal on Semantic Web and Information Systems (IJSWIS), 2013, vol. 9, issue 2, 1-30

Abstract: Collaborative tagging has emerged as a common solution for labelling and organising online digital content. However, collaborative tagging systems typically suffer from a number of issues such as tag scarcity or ambiguous labelling. As a result, the organisation and browsing of tagged content is far from being optimal. In this work the authors present a general scheme for building a folksonomy-based tag recommendation system to help users tagging online content resources. Based on this general scheme, the authorse describe eight tag recommendation methods and extensively evaluate them with data coming from two real-world large-scale datasets of tagged images and sound clips. Their results show that the proposed methods can effectively recommend relevant tags, given a set of input tags and tag co-occurrence information. Moreover, the authors show how novel strategies for selecting the appropriate number of tags to be recommended can significantly improve methods performances. Approaches such as the one presented here can be useful to obtain more comprehensive and coherent descriptions of tagged resources, thus allowing a better organisation, browsing and reuse of online content. Moreover, they can increase the value of folksonomies as reliable sources for knowledge-mining.

Date: 2013
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