Abstract
Semantic Web data is increasing day by day. The important issue of this web is to handle inordinate volume of information that has many other challenges like query processing and optimisation over widely distributed RDF data. The proposed approach use the reduced querying cost, and hereby optimising the execution time of the query. Optimization of query is one of the most popular problems existing in RDF data which is among the hardest combinatorial optimization problem. Our finding and experimental result concludes that TLBO(Teaching Learning Based Optimisation) outperforms in terms of execution time of the query when compare with ACO variants. In experiment, different types of queries are taken into account like chain, star to show the results of execution time taken by query. This approach centered on main-memory RDF data model.
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