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Volumn 1, Issue , 2010, Pages

Data quality improvement using fuzzy association rules

Author keywords

Data mining; Data quality; Fuzzy association rules

Indexed keywords

AUTOMATIC METHOD; CORRECTION OF ERRORS; DATA ANALYSIS; DATA DEFECTS; DATA MINING METHODS; DATA QUALITY; DATA REFINEMENTS; DATA SETS; DOMAIN EXPERTS; FUZZY ASSOCIATION RULE;

EID: 78049323851     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICEIE.2010.5559676     Document Type: Conference Paper
Times cited : (11)

References (9)
  • 6
    • 78049341293 scopus 로고    scopus 로고
    • Data quality mining: Employing classifiers for assuring consistent datasets
    • Springer-Verlag Berlin Heidelberg
    • F. Grüning, "Data Quality Mining: Employing Classifiers for Assuring consistent Datasets", Proc. of the 21-th Information Technologies in Environmental Engineering, Springer-Verlag Berlin Heidelberg, pp. 58-94, 2007.
    • (2007) Proc. of the 21-th Information Technologies in Environmental Engineering , pp. 58-94
    • Grüning, F.1
  • 7
    • 80053137024 scopus 로고    scopus 로고
    • Data quality management: The most critical initiative you can implement
    • Inc. Boulder
    • J. Geiger, "Data Quality Management: The Most Critical Initiative You Can Implement", Intelligent Solutions, Inc., Boulder, Paper 098-29, 2004.
    • (2004) Intelligent Solutions , pp. 098-129
    • Geiger, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.