Query Optimization in Kess - An Ontology-Based KBMS Henrique Andrade and Joel Saltz   View Paper (PDF)   Return to Query Languages and Optimization Abstract This paper presents an approach for the implementation of query optimization techniques in Kess (the Knowledge Enhanced SQL Server). Kess is a Knowledge Database Management System (KBMS) that uses a semantic ontology-based data model. We have classified our query optimization techniques in two different categories: 1. semantic-based and 2. data access path related. These techniques use a compiler optimization approach to simplify query predicates and use caching to optimize memory hierarchy performance for the evaluation of ontology-related predicates. This work also presents the performance analysis of the implementation of such optimizations in Kess in the form of a performance analysis. DiSC'01 Copyright ©2002 ACM Inc.