Recommender systems are today common on online news sites and shopping sites. The systems take into account the user's preferences and/or similarities with other users, but are otherwise indifferent to the user's context.
In this project we will investigate how recommender systems may be used to manage the pools of a river and recommend the most suitable pools to individual anglers. Both time and location need to be used as part of the recommender strategies. Information sources are maps with indicated pools, online data about pool bookings and catch statistics, and local news about fishing.