Fans who want to read fanfiction will invariably find themselves at the massive, community-supported, volunteer-run Archive of Our Own (or AO3 for short). This Hugo award-winning, open-source based website archives over 6 million fanworks, for over 5 million registered users in 35,000 fandoms. As a community-run and community-focused non-profit, it does a stellar job of its primary function, which is saving and collating amateur works. However, beyond essential filtering functions, it provides no methods of recommending works to users.
I wanted to provide an alternate method for fans to find new works and developed a recommender system to do just that at fanrecs.com. AO3 users have the option of leaving kudos on fanworks (fan-created items like fiction, art, videos, or commentary). These kudos are the basis for an item to item, implicit, collaborative filtering based model. Hosted on a web-based microservice, one can enter in the id of a favorite work and get suggestions for other works they might enjoy.
Currently recommendations are only on a subset of works (namely, Star Wars fandom circa May 2020) while I work out a way to scale the recommendations beyond 125k fics. Details on implementation can be found in my GitHub repository