Query By Example (QBE) tries to make database interactions easier for non-technical users. Using QBE, users can retrieve information from (large) databases using data examples that characterize their intent. The quality of the results produced by QBE systems critically depends on the data examples provided by the user. This Master Thesis project aims to explore the use of Recommender Systems-like techniques to improve the way non-technical users provide examples to QBE systems. A particular interest in this project is the investigation of how to enhance example diversity so that they can better characterize the user's intent.