Yep, I am working on this, and it is a lot of how our system works under the surface. It just isn't accurate enough yet. I do use the LOC data, but only a very

Yep, I am working on this, and it is a lot of how our system works under the surface. It just isn't accurate enough yet. I do use the LOC data, but only a very small % of books have that. I also use a NLP/ML tool called Wikifier that connects books to Wikidata topics as I want to use that data to help build knowledge graphs so readers can browse a timeline of WW2 and also see books on those subjects. What is the problem? With the topic system, it just isn't quite accurate enough; once I switch over to the newer AI systems later this year, it should work better. With the genre system, the big problem is that the BISAC publishing genre system is being abused by publishers. So, the data is not reliable because of abuse and ignorance. For example, I have thousands of books marked nonfiction and fiction because the publisher doesn't know how to use the system and picks nonfiction topics for a fiction book. Or, a publisher picks a book for a genre it doesn't belong in because they think it will get them more sales. It is really frustrating and I am spending a huge chunk of my time this year to look at how I can fix it. It probably means ignoring this system and using AI to classify it with other data we have.