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Number 3

Proposing an Improved Semantic and Syntactic Data Quality Mining Method using Clustering and Fuzzy Techniques

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  • International Journal of Applied Information Systems
  • Foundation of Computer Science (FCS), NY, USA
  • Volume 3 - Number 3
  • Year of Publication: 2012
  • Authors: Hamid Reza Khosravani
  • http:/ijais12-450475
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  • Hamid Reza Khosravani 2012. Proposing an Improved Semantic and Syntactic Data Quality Mining Method using Clustering and Fuzzy Techniques. International Journal of Applied Information Systems. 3, 3 (July 2012), 8-12. DOI=http://dx.doi.org/10.5120/ijais450475 
  • @article{10.5120/ijais2017451568,
author = {Hamid Reza Khosravani},
title = {Proposing an Improved Semantic and Syntactic Data Quality Mining Method using Clustering and Fuzzy Techniques},
journal = {International Journal of Applied Information Systems},
issue_date = {July 2012},
volume = {3},
number = {},
month = {July},
year = {2012},
issn = {},
pages = {8-12},
numpages = {},
url = {/archives/volume3/number3/210-0475},
doi = { http:/ijais12-450475},
publisher = { xA9 2010 by IJAIS Journal},
address = {}
}

  • %1 450475
%A Hamid Reza Khosravani
%T Proposing an Improved Semantic and Syntactic Data Quality Mining Method using Clustering and Fuzzy Techniques
%J International Journal of Applied Information Systems
%@ 
%V 3
%N 
%P 8-12
%D 2012
%I  xA9 2010 by IJAIS Journal

Abstract

Data quality plays an important role in knowledge discovering process in databases. Researchers have proposed two different approaches for data quality evaluation so far. The first approach is based on statistical methods while the second one uses data mining techniques which caused further improvement in data quality evaluation results through relying on knowledge extracting. Our proposed method in data quality evaluation follows the second approach and focuses on accuracy dimension of data quality evaluation including both syntactic and semantic aspects.

References

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Keywords

Data Quality Mining, Association Rules, Categorical Feature, Numerical Feature

Index Terms

Computer Science
Information Sciences