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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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A novel adaptive Cuckoo search for optimal query plan generation.

Ramalingam Gomathi1, Dhandapani Sharmila2

  • 1Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam 638401, India.

Thescientificworldjournal
|September 13, 2014
PubMed
Summary

This study introduces an adaptive Cuckoo search (ACS) algorithm to optimize queries for large Resource Description Framework (RDF) graphs, significantly reducing execution time for semantic web data.

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Area of Science:

  • Computer Science
  • Semantic Web Technologies
  • Artificial Intelligence

Background:

  • The increasing volume of web pages necessitates efficient semantic web technologies.
  • Resource Description Framework (RDF) is a W3C standard for semantic web data.
  • Traditional query optimization methods struggle with large RDF graphs.

Purpose of the Study:

  • To address the challenge of query optimization for large RDF graphs.
  • To design an efficient algorithm for querying semantic web data.
  • To improve the execution time of queries on RDF data.

Main Methods:

  • Development of an adaptive Cuckoo search (ACS) algorithm.
  • Application of ACS for querying and generating optimal query plans for large RDF graphs.
  • Experimental evaluation on diverse datasets with varying numbers of predicates.

Main Results:

  • The proposed adaptive Cuckoo search (ACS) algorithm demonstrated significant improvements in query execution time.
  • Experimental results confirm the efficiency of ACS for optimizing semantic web data queries.
  • The algorithm's performance was validated across different dataset sizes and complexities.

Conclusions:

  • The adaptive Cuckoo search (ACS) algorithm is an effective approach for optimizing queries on large RDF graphs.
  • This research contributes a novel metaheuristic solution to semantic web data query optimization.
  • The findings suggest ACS as a viable alternative to traditional query optimization methods.