Acta Scientific Computer Sciences

Review Article Volume 3 Issue 1

TaQO: A Tabu Search Based SPARQL Query Optimization Approach

Tanvi Chawla*

Research Scholar, MNIT, Jaipur, India

*Corresponding Author: Tanvi Chawla, Research Scholar, MNIT, Jaipur, India.

Received: August 04, 2021; Published: December 13, 2021

Abstract

Semantic Web is an emerging technology for information representation in web pages. This growth has further accelerated with the Linked Open Data (LOD) movement. One of the commonly accepted standard for representing semantic web data is the Resource Description Framework (RDF). SPARQL Protocol and RDF Query Language (SPARQL) is the commonly used query language for querying data from the Semantic Web. Query Processing is one of the most important tasks of any database and thus it requires optimal solutions. Query Optimization is one of the phases in query processing. This phase is crucial for generating an optimed version to a submitted query. This optimized query will reduce the query execution time depending upon the type of optimization solution used. The generally used solutions to Query optimizations like those used for relational databases can be directly applied to Semantic web frameworks. But these solutions have to be tailored according to RDF data and SPARQL.

 

Keywords: Semantic Web; RDF; SPARQL; Query Optimization; Selectivity

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Citation

Citation: Tanvi Chawla. “TaQO: A Tabu Search Based SPARQL Query Optimization Approach". Acta Scientific Computer Sciences 3.1 (2022): 16-22.

Copyright

Copyright: © 2022 Tanvi Chawla. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




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