A cost model for similarity queries in metric spaces
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Optimization for Spatial Query Processing
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
SIREN: a similarity retrieval engine for complex data
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Efficient processing of complex similarity queries in RDBMS through query rewriting
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
MAMCost: Global and Local Estimates leading to Robust Cost Estimation of Similarity Queries
SSDBM '07 Proceedings of the 19th International Conference on Scientific and Statistical Database Management
Seamlessly integrating similarity queries in SQL
Software—Practice & Experience
Similarity queries: their conceptual evaluation, transformations, and processing
The VLDB Journal — The International Journal on Very Large Data Bases
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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.