Preference queries incorporate the notion of binary preference relation into relational database querying. Instead of returning all the answers, such queries return only the best answers, according to a given preference relation. Preference queries a
re a fast growing area of database research. Skyline queries constitute one of the most thoroughly studied classes of preference queries. A well known limitation of skyline queries is that skyline preference relations assign the same importance to all attributes. In this work, we study p-skyline queries that generalize skyline queries by allowing varying attribute importance in preference relations. We perform an in-depth study of the properties of p-skyline preference relations. In particular,we study the problems of containment and minimal extension. We apply the obtained results to the central problem of the paper: eliciting relative importance of attributes. Relative importance is implicit in the constructed p-skyline preference relation. The elicitation is based on user-selected sets of superior (positive) and inferior (negative) examples. We show that the computational complexity of elicitation depends on whether inferior examples are involved. If they are not, elicitation can be achieved in polynomial time. Otherwise, it is NP-complete. Our experiments show that the proposed elicitation algorithm has high accuracy and good scalability
The binary relation framework has been shown to be applicable to many real-life preference handling scenarios. Here we study preference contraction: the problem of discarding selected preferences. We argue that the property of minimality and the pres
ervation of strict partial orders are crucial for contractions. Contractions can be further constrained by specifying which preferences should be protected. We consider two classes of preference relations: finite and finitely representable. We present algorithms for computing minimal and preference-protecting minimal contractions for finite as well as finitely representable preference relations. We study relationships between preference change in the binary relation framework and belief change in the belief revision theory. We also introduce some preference query optimization techniques which can be used in the presence of contraction. We evaluate the proposed algorithms experimentally and present the results.
