A distributed content item recommendation system comprises a central recommendation server (101) and a plurality of remote recommendation devices (103) coupled to the central recommendation server (101) via a communication network (105). The central recommendation server (101) stores content item set correlation data for sets of content items. The correlation data is used for item based collaborative filtering in recommendation processors (303) of the recommendation devices (103). A computation task processor (207) maintains a task list of content item correlation computation tasks which can be independently executed to generate content item set correlation data. A task assignment processor (209) can assign the computation tasks to remote recommendation devices (103) which comprise a processing unit (307) that calculates the associated correlation data and returns it to the recommendation server (101). The distributed recommendation system thus uses distributed computation of centrally stored correlation data thereby substantially reducing the cost and complexity of the recommendation server and/or improves the recommendations.