Self-adaptive recommendation systems: Models and experimental analysis

We design and study recommendation algorithms for a fully decentralized scenario in which each item/node of a network recommends other items/nodes only on the basis of simple statistics on the behaviour of users that visited the node in the past. We perform a theoretical and experimental study assessing that very simple heuristics can provide recommendations of good quality even in such a restrictive scenario. © 2008 IEEE