an efficient framework for similarity query optimization
The increasing volume of multimedia data stored in relational database management systems (RDBMS) demands efficient ways to process similarity queries. Therefore, the query processor should provide mechanisms to express similarity queries, to interpret and translate them into equivalent expression in relational algebra, to evaluate alternative query plans and finally to execute the queries using the best plan found. In this paper, we present an effective framework to interpret, translate, select the best plan and efficiently execute similarity queries over data indexed by metric access methods. Experimental evaluation of the framework shows a reduction of up to 20\% in the total time required to answer similarity queries.
query optimization similarity algebra query processing