Abstract

Information integration systems provide uniform interfaces to varieties of heterogeneous information sources. Our work focuses on query answering in such system. The current generation of query answering algorithms in local-as-view (source-centric) information integration systems all produce what has been thought of as "the best obtainable" answer, given the circumstances that the source-centric approach introduces incomplete information into the virtual global relations. However, this "best obtainable" answer does not include all information that can be extracted form the sources because it does not allow partial information. We define the semantics of partial facts and introduce the notion of exact answer--that is the answer that includes partial facts. We also present two methods for computing exact answer, in such way that semantics of queries remain compositional. The first method is tableau-based and is a generalization of the "inverse-rules" approach. The second, much more efficient method, is a generalization of the rewriting approach, and is based on partial containment mappings introduced in the thesis. Furthermore, we provide two query rewriting algorithms that can be used to compute exact answer. Finally, we present experimental results confirming that computation of the exact answer can be done efficiently for all practical situations including the large-scale systems