%0 Journal Article
%T Data Quality Measurement on Categorical Data Using Genetic Algorithm
%A J.Malar Vizhi
%A T.Bhuvaneswari
%J International Journal of Data Mining & Knowledge Management Process
%D 2012
%I Academy & Industry Research Collaboration Center (AIRCC)
%X Data quality on categorical attribute is a difficult problem that has not received as much attention asnumerical counterpart. Our basic idea is to employ association rule for the purpose of data qualitymeasurement. Strong rule generation is an important area of data mining. Association rule miningproblems can be considered as a multi objective problem rather than as a single objective one. The mainarea of concentration was the rules generated by association rule mining using genetic algorithm. Theadvantage of using genetic algorithm is to discover high level prediction rules is that they perform a globalsearch and cope better with attribute interaction than the greedy rule induction algorithm often used indata mining. Genetic algorithm based approach utilizes the linkage between association rule and featureselection. In this paper, we put forward a Multi objective genetic algorithm approach for data quality oncategorical attributes. The result shows that our approach is outperformed by the objectives like accuracy,completeness, comprehensibility and interestingness.
%K Association Rule
%K Categorical attributes
%K Data Mining
%K Data Quality mining
%K Genetic Algorithm.
%U http://airccse.org/journal/ijdkp/papers/2112ijdkp03.pdf