Collaborative Filtering & Recommender Systems
Summary
Recommender systems are now setting the pace in the digital marketplace – not just for products and services, but also in networking sites which present users with a choice of people that they could connect with. Facebook’s Maja Kabiljo & Aleksandar Ilic have written about how they use both Alternating Least Squares (ALS) and Stochastic gradient descent (SGD) optimization in a customized rotational hybrid method to help achieve better recommendations. They found that using the standard method led to problems such as large network traffic and skewed item degree distribution. At LinkedIn item-to-item collaborative filtering is used to set up recommendations for people, job, company, group and is one of the principal components of user engagement. The Browsemaps platform which is a hybrid offline/online system enables rapid development, deployment, and computation of collaborative filtering recommendations.
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