Model Generation in Disjunctive Normal Databases
Adnan H. Yahya · 1996
Algorithms for computing several classes of models for disjunctive normal databases are presented. We show how to efficiently compute minimal, restricted minimal, perfect, and stable models. The common feature of the advanced algorithms is that they are based on augmenting a model generating procedure with a set of hypotheses to guide its search for acceptable models and/or to interpret negation in clause bodies. The approach is shown to be useful for different database applications including query answering under different semantics and integrity constraint enforcement. The developed algorithms are easy to implement and compare favorably with others advanced in the literature for the same purpose. 1 Introduction Much attention has been devoted to computing models for disjunctive databases as a tool for data storage and manipulation. Several algorithms were suggested for computing different classes of models that can also be utilized for query answering and integrity constraint enforc...