desc2tag: A Reinforcement Learning Approach to Mashup Tag Recommendation

Abstract

Tags are critical sources of data for search, browsing and information retrieval. Manual selection of tags, over the years, have not been very effective. This paper introduces an approach to automatic mashup tag recommendation, based on reinforcement learning (RL). Our RL approach is able to carry out effective exploratory actions to automatically extract the and recommend tags for mashups. We perform experiments to evaluate our proposed method. Results from our experiments show that, the recommended mashup tags improve performance on the information retrieval task.