@article{(Open Science Index):https://publications.waset.org/pdf/9999468,
	  title     = {A Hybrid Nature Inspired Algorithm for Generating Optimal Query Plan},
	  author    = {R. Gomathi and  D. Sharmila},
	  country	= {},
	  institution	= {},
	  abstract     = {The emergence of the Semantic Web technology
increases day by day due to the rapid growth of multiple web pages.
Many standard formats are available to store the semantic web data.
The most popular format is the Resource Description Framework
(RDF). Querying large RDF graphs becomes a tedious procedure
with a vast increase in the amount of data. The problem of query
optimization becomes an issue in querying large RDF graphs.
Choosing the best query plan reduces the amount of query execution
time. To address this problem, nature inspired algorithms can be used
as an alternative to the traditional query optimization techniques. In
this research, the optimal query plan is generated by the proposed
SAPSO algorithm which is a hybrid of Simulated Annealing (SA)
and Particle Swarm Optimization (PSO) algorithms. The proposed
SAPSO algorithm has the ability to find the local optimistic result
and it avoids the problem of local minimum. Experiments were
performed on different datasets by changing the number of predicates
and the amount of data. The proposed algorithm gives improved
results compared to existing algorithms in terms of query execution
time.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {8},
	  number    = {8},
	  year      = {2014},
	  pages     = {1519 - 1524},
	  ee        = {https://publications.waset.org/pdf/9999468},
	  url   	= {https://publications.waset.org/vol/92},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 92, 2014},
	}