2018
DOI: 10.5815/ijcnis.2018.03.06
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Optimization of Different Queries using Optimization Algorithm (DE)

Abstract: The biggest challenge in modern web is to tackle tremendous growth of data, scattered and continuously updating in nature. Processing of such unscattered data by human or machine remains a tedious task. Semantic Web; as a solution has already been invented. But, still there are some other challenges, like as optimization of the query. We introduce a new approach for real-time SPARQL query optimization with different forms and different triple patterns. The strategy introduces rearrangement of order of triple p… Show more

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Cited by 4 publications
(3 citation statements)
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“…Various evolutionary optimization algorithms such as Ant Colony Optimization (ACO), two-phase optimization, and Genetic Algorithm (GA) for optimizing chain queries were compared in the research. Saharan et al [8] invented a solution to address the querying of scattered data using Differential Evolution. The algorithm uses the policy of reorganization of the order of triples pattern.…”
Section: A Review Of Literaturementioning
confidence: 99%
“…Various evolutionary optimization algorithms such as Ant Colony Optimization (ACO), two-phase optimization, and Genetic Algorithm (GA) for optimizing chain queries were compared in the research. Saharan et al [8] invented a solution to address the querying of scattered data using Differential Evolution. The algorithm uses the policy of reorganization of the order of triples pattern.…”
Section: A Review Of Literaturementioning
confidence: 99%
“…S. Saharan, J. S. Lather, and R. Radhakrishnan [15] proposed a new method for the optimization of the SPARQL query with various triple patterns. The Differential Evolution (DE) applied for the triple pattern rearrange in order.…”
Section: Related Workmentioning
confidence: 99%
“…The DE is a simple and effective algorithm that has a small number of adjustable control parameters. It has been successfully used in many engineering applications of several fields such as neural networks, signal processing, pattern recognition, image processing, bioinformatics, control systems, robotics, wireless communications, and semantic web [2][3][4][5][6][7][8]. Exploration and exploitation abilities of any populationbased optimization algorithm play a vital role in enhancing its accuracy and convergence speed [9].…”
Section: Introductionmentioning
confidence: 99%