Preference-driven query processing

We propose a partition-based framework for evaluating preference queries. The framework is independent of how partitions are generated, and returns answers progressively as the query is being evaluated. We evaluated the framework using partitions obtained from the leaf nodes of R-trees. Our study shows that our approach can shorten the initial response time.