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Recommender systems have become important tools to support users inidentifying relevant content in an overloaded information space. To ease thedevelopment of recommender systems, a number of recommender frameworks havebeen proposed that serve a wide range of application domains. Our TagRecframework is one of the few examples of an open-source framework tailoredtowards developing and evaluating tag-based recommender systems. In this paper,we present the current, updated state of TagRec, and we summarize and reflecton four use cases that have been implemented with TagRec: (i) tagrecommendations, (ii) resource recommendations, (iii) recommendationevaluation, and (iv) hashtag recommendations. To date, TagRec served thedevelopment and/or evaluation process of tag-based recommender systems in twolarge scale European research projects, which have been described in 17research papers. Thus, we believe that this work is of interest for bothresearchers and practitioners of tag-based recommender systems.

The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems