A New Top-k Conditional XML Preference Queries

Abstract

Preference querying technology is a very important issue in a variety of applications ranging from ecommerce to personalized search engines. Most of recent research works have been dedicated to this topic in the Artificial Intelligence and Database fields. Several formalisms allowing preference reasoning and specification have been proposed in the Artificial Intelligence domain. On the other hand, in the Database field the interest has been focused mainly in extending standard Structured Query Language (SQL) and also eXtensible Markup Language (XML) with preference facilities in order to provide personalized query answering. More precisely, the interest in the database context focuses on the notion of Top-k preference query and on the development of efficient methods for evaluating these queries. A Top-k preference query returns k data tuples which are the most preferred according to the user's preferences. Of course, Top-k preference query answering is closely dependent on the particular preference model underlying the semantics of the operators responsible for selecting the best tuples. In this paper, we consider the Conditional Preference queries (CP-queries) where preferences are specified by a set of rules expressed in a logical formalism. We introduce Top-k conditional preference queries (Top-k CP-queries), and the operators BestK-Match and Best-Match for evaluating these queries will be presented.