Folksonomy-based Tag Recommendation for Online Audio Clip Sharing

Collaborative tagging has emerged as an efficient way to semantically describe online resources shared by a community of users. However, tag descriptions present some drawbacks such as tag scarcity or concept inconsistencies. In these situations, tag recommendation strategies can help users in adding meaningful tags to the resources being described. Freesound is an online audio clip sharing site that uses collaborative tagging to describe a collection of more than 140,000 sound samples. In this paper we propose four algorithm variants for tag recommendation based on tag co-occurrence in the Freesound folksonomy. On the basis of removing a number of tags that have to be later predicted by the algorithms, we find that using ranks instead of raw tag similarities produces statistically significant improvements. Moreover, we show how specific strategies for selecting the appropriate number of tags to be recommended can significantly improve algorithms’ performance. These two aspects provide insight into some of the most basic components of tag recommendation systems, and we plan to exploit them in future real-world deployments.