Description
Typically when you think about using a topic model in production you encounter two hurdles: First, topics change continually, and document tags become stale as soon as they are created. Second, while unsupervised topic models do a good job of clustering topics, creating robust, human-interpretable labels is challenging. Framing topic modeling as a search problem, helps overcome these challenges and makes it easier to use supervised or unsupervised topic models in real-time applications.