Users often can not easily express their queries. For example, in a multimedia image by content setting, the user might want photographs with sunsets; in current systems, like QBIC, the user has to give a sample query, and to specify the relative importance of color, shape and texture. Even worse, the user might want correlations between attributes, like, for example, in a traditional, medical record database, a medical researcher might want to nd mildly overweight patients", where the implied query would be weight height 4lb inch". Our goal is to provide a user-friendly, but theoretically solid method, to handle such queries. We allow the user to give several examples, and, optionally, their 'goodness' scores, and we propose a novel method to guess" which attributes are important, which correlations are important, and with what weight. Our contributions are twofold: a we formalize the problem as a minimization problem and show how to solve for the optimal sol...