CONSTRUCTING PARTIAL AND COMPLETE INTELLIGENT ANSWERS FOR RECURSIVE QUERIES

Abstract

In this paper we study the issue of providing intelligent answers to recursive queries initially proposed in [Imie88]. In contrast to conventional query answers, which are sets of tuples, intelligent answers are rules describing the characteristics of the results. This way, an intelligent answer facilitates users to better capture the meaning of the query. To this aim, we first extend the notion of intelligent answers by allowing them to be partial (or incomplete). Complete and partial intelligent answers are both useful, in that they provide (possibly partial) characterizations of queries. We will show that complete intelligent answers also give a more efficient way to evaluate queries. For constructing intelligent answers, we propose a general approach that enables us to combine several cases studied in [Imie88]. Moreover, we will show that semantic constraints can be systematically utilized to provide complete intelligent answers to a wider range of queries. We consider two commonly used classes of semantic constraints called implication and referential constraints, and prove that the completeness of intelligent answers with respect to semantic constraints can be reduced to the semantics-based query containment problem. Finally, a necessary and sufficient condition is given to solve this containment problem.