A fastText-based hybrid recommender

Facebook Research’s new fastText library can learn the meaning of metadata from the text it labels. By labelling documents with the users who read them, we used fastText to hack together a “hybrid recommender” system, able to recommend documents to users using both collaborative information (“people who read this also liked that”) and whether the text in the documents is thematically similar to things they read previously. Early signs are it performs quite well, so we’ll continue to experiment with it.

Give me five


Give me five is an open source Chrome extension that allows you to recommend the content you push to Lateral based on the content of the page you’re currently visiting. It’s the same code base that the NewsBot Chrome extension is built upon. The screencast shows the extension in action: You can find the source code […]

Article Extractor API


Today we are pleased to announce the release of our Article Extractor API! When recommending content it’s important to ensure you are only recommending for the relevant text of an article. We have often faced this challenge with online articles and blogs. We’d want to fetch a URL but just extract the main body of […]