Valve just released a brand new update to Steam, that being the Steam Interactive Reccomender. This will help streamline recommendations to you from your account purchases, etc. You can learn more about it below.
Today we released the Steam Interactive Recommender, a way for users to harness the power of machine learning to discover personalized, interactive recommendations, based on your patterns of play. Along with powerful tag-based filters, you can tailor your results on the fly, selecting your own balance of popular or niche, and recent or classic titles, to find just the right games you’re in the mood to play.
Recommendations generated by the system will appear on your store homepage. The Explore and Customize button leads to the full Interactive Recommender, where you can adjust parameters and save settings. Any customizations you make will also be used on the homepage.
The Interactive Recommender uses a machine learning model that is trained based on the playtime histories of millions of Steam users. It’s not directly affected by tags or reviews—it instead learns about the games on Steam by looking at what users actually play. The basic idea is that if there are other players with similar play habits to you, who also play a game that you haven’t tried yet, then that game is likely to be one you’ll enjoy too.
We’re also starting to apply the underlying model in other parts of the Steam store, where we think it can help players see the most relevant content or make more informed choices. For example, when viewing the page for a particular game, you may sometimes see “Players like you love this game” shown as a reason why the game is relevant to you, alongside other factors.
