Reordering Triple Patterns of Sparql Queries Using Ant Colony Optimization

Abstract

Semantic web is a paradigm that is proposed for configuring and controlling the overwhelming volumes of information on the web. One important challenge in semantic web is decreasing execution times of queries. Reordering triple patterns is an approach for decreasing execution times of queries. In this study, an ant colony optimization approach for optimizing SPARQL queries by reordering triple patterns is proposed. Contributions of this approach are optimizing order of triple patterns in SPARQL queries using ant colony optimization for lesser execution time and real time optimization without requiring any prior domain knowledge. This proposed novel method is implemented using ARQ query engine and it optimizes the queries for in-memory models of ontologies. Experiments show that proposed method reduces execution time considerably.