Unsupervised extreme multi label classification of stack overflow posts
Peter Devine, Kelly Blincoe · 2022
Knowing the topics of a software forum post, such as those on StackOverflow, allows for greater analysis and understanding of the large amounts of data that come from these communities. One approach to this problem is using extreme multi label classification (XMLC) to predict the topic (or "tag") of a post from a potentially very large candidate label set. While previous work has trained these models on data which has explicit text-to-tag information, we assess the classification ability of embedding models which have not been trained using such structured data (and are thus "unsupervised") to assess the potential applicability to other forums or domains in which tag data is not available.