![]() "We don't explicitly feed our model information about the games. Valve also says they discard most category information about the game when entering it into their model. The model then recommends titles the user might enjoy based on other games played by like-minded Steam users. Rather than base recommendations around genre or category, the Interactive Recommender instead scans through Valve's data sets to find other Steam users with similar tastes. Valve says the Interactive Recommender uses a "neural-network model that is trained to recommend games based on a user's playtime history, along with other salient data." The data is modified by two sliders that users can edit: one ranges from "popular" to "niche," while the other slider ranges from "older" to "newer" games. As Valve's Steam Labs launch three new experimental features today, one has caught the interest of many Steam users: its new algorithm for game recommendations based on Valve's machine learning technology.
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