Recommendation systems are one of the most widely adopted machine learning (ML) technologies in real-world applications, ranging from social networks to ecommerce platforms. Users of many online systems rely on recommendation systems to make new friendships, discover new music according to suggested music lists, or even make ecommerce purchase decisions based on the recommended products. In social networks, one common use case is to recommend new friends to a user based on the users’ other connections. Users with common friends likely know each other. Therefore, they should have a higher score for a recommendation system to propose if they haven’t been connected yet.
Social networks can naturally be expressed in a graph, where the nodes represent people, and the connections between people, such as friendship or co-workers, are represented by edges. The following illustrates one such social network. Let’s imagine that we have a social network with the members (nodes)

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