Extracting metadata from our documents is an important part of our discovery and recommendation pipeline, but discerning useful and relevant details from text-heavy user-uploaded documents can be challenging. This is part 2 in a series of blog posts describing a multi-component machine learning system the Applied Research team built to extract metadata from our documents in order to enrich downstream discovery models. In this post, we present the challenges and limitations the team faced when...
