A SYSTEM AND METHOD FOR RECOMMENDING ITEMS IN A SOCIAL NETWORK

摘要

The present principles consider stochastic bandits with side observations, a model that accounts for both the exploration/ exploitation dilemma and relationships between arms. In this setting, after pulling an arm i, the decision maker also observes the rewards for some other actions related to i. The present principles provide a method and a system for efficiently leveraging additional information based on the responses provided by other users connected to the user via a computerized social network and derive new bounds improving on standard regret guarantees. We will see that this model is suited to content recommendation in social networks, where users' reactions may be endorsed or not by their friends.