As nowadays massive amounts of data are stored in database systems, it becomes more and more difficult for a database user to exactly retrieve data that are relevant to him: it is not easy to formulate a database query such that, on the one hand, the user retrieves all the answers that interest him, and, on the other hand, the user does not retrieve too much irrelevant data.

A flexible query answering mechanism automatically searches for informative answers: it offers the user information that is close to (but not too far away from) what the user intended. In this talk, we show how to apply generalization operators to queries; this results in a set of logically more general queries which might have more answers than the original query.

A similarity-based or a weight-based strategy can be used to obtain only answers close to the user's interest.