#1: Practical Recommender Systems with Kim Falk
Recsperts - Recommender Systems Experts
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Collaborative Filtering in Recommendation Systems
Content recommendation is based on similarities in user preferences and consumption behavior rather than purely item attributes. Collaborative filtering can be user-based, where recommendations are made based on similar users' preferences, or item-based, where items are recommended based on their similarity to items previously consumed by the user. In collaborative filtering, users are clustered into small groups with similar tastes, allowing for personalized recommendations based on the collective preferences of those in the group. This approach leverages the idea that users with similar tastes are likely to enjoy items that others in their group have consumed but the given user has not yet experienced.
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