Finding Improved Frequent Data Query Sets using Genetic Algorithm |
Author(s): |
| Shankey Gupta , Doon Valley Institute of Engineering And Technology (DIET); Amrita Chaudhary, Doon Valley Institute of Engineering And Technology (DIET) |
Keywords: |
| Data Mining, Web Mining, Apriori Algorithm, Genetic Algorithm (GA) |
Abstract |
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In the recent years, several methods are proposed for mining frequent data query sets, but almost all of them suffer from the problems like generating large number of candidate generation and large number of database scans. The proposed approach uses Genetic Algorithm to produce offsprings (under certain fitness test or conditions) to become frequent pattern and then these offsprings become ancestor for next query set. The proposed approach requires only one scan of the database and also this approach pruned the useless individuals or candidates in less time. Experimental results shows that the proposed approach worked better than existing approach using MATLAB programming. |
Other Details |
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Paper ID: IJSRDV3I41053 Published in: Volume : 3, Issue : 4 Publication Date: 01/07/2015 Page(s): 1988-1992 |
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