International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 179 - Issue 7 |
Published: Dec 2017 |
Authors: G. Gunasekaran, S. Murugan |
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G. Gunasekaran, S. Murugan . Dynamic Memory Efficient Frequent Pattern Growth for Data Excavation. International Journal of Computer Applications. 179, 7 (Dec 2017), 32-40. DOI=10.5120/ijca2017915973
@article{ 10.5120/ijca2017915973, author = { G. Gunasekaran,S. Murugan }, title = { Dynamic Memory Efficient Frequent Pattern Growth for Data Excavation }, journal = { International Journal of Computer Applications }, year = { 2017 }, volume = { 179 }, number = { 7 }, pages = { 32-40 }, doi = { 10.5120/ijca2017915973 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2017 %A G. Gunasekaran %A S. Murugan %T Dynamic Memory Efficient Frequent Pattern Growth for Data Excavation%T %J International Journal of Computer Applications %V 179 %N 7 %P 32-40 %R 10.5120/ijca2017915973 %I Foundation of Computer Science (FCS), NY, USA
Advancements in information technology increase the data volume of many domains into manyfold. Dynamic Memory Efficient Frequent Pattern (DMEFP) technique introduces new methods to represent data and redundant frequent patterns. Introduction of Repeat Pattern Table (RPT) and new node type ‘Tree Pattern Node’ (TPN) in frequent pattern tree softens the data mining process to be performed in a modern way. DMEFP technique comprises new rules to aggregate pattern nodes and RPT. Computational resources are used sagely in DMEFP technique for data mining. Reduced resource consumption helps to parse large amount of data in short time durations without much complexity.