f2tag — Can Tags be Predicted Using Formulas?

The appropriate tagging of questions on Q&A networks like StackExchange is important for organizing the content of these platforms. Accordingly, recommender systems can help the users by suggesting relevant tags for their questions. The data used as input to these recommender systems can be manifold like headlines of the questions or their entire content. In this work, we explore whether mathematical formulas alone are sufficient for predicting tags of mathematical questions. To achieve this goal, we employ and compare well established methods on both textual and visual representations of formulas. To the best of our knowledge, we are the first to use this kind of limited content as input. Our results show that formulas are helpful for finding proper tags while visual representations outperform textual ones.