Open topics for students: Recommendations

With the growing complexity of the Web, users often find themselves overwhelmed by the mass of choices available. Shopping for DVDs, books or clothes online becomes more and more difficult, as the variety of offers increases rapidly and gets unmanageable. To facilitate users in their selection process, recommender systems provide suggestions on items, which might be interesting for the respective user. In particular, recommender systems aim at giving recommendations to users or groups of users by estimating their item preferences and recommending those items featuring the maximal predicted preference. The prerequisite for determining such recommendations is historical information on the users’ interests, e.g., the users’ purchase history.