Optimization of tag recommender systems in a real life setting

The purpose of this article is to describe the performance related features of our tag recommending Web service. The service is one of several systems currently integrated with multiplexing recommender framework for Bibsonomy.org bookmarking portal. The framework was introduced during ECML PKDD Discovery Challenge 2009. Due to good balance between speed and quality of our recommendations we managed to outperform other systems according to one of three most important evaluation measures i.e. the proportion of correctly recommended tags that have been clicked by a user.