Measuring and modelling data quality for quality-awareness in data mining

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

This chapter presents an overview of data quality management, data linkage and data cleaning techniques that can be advantageously employed for improving the quality awareness of the knowledge discovery process. Based on this database-oriented overview of data quality management, this chapter also presents a pragmatic step-by-step framework for data quality awareness and enhancement before warehousing and during the knowledge discovery process. Each step may use, combine and exploit the data quality characterization, measurement and management methods, and the related techniques proposed in the literature.

Original languageEnglish
Pages (from-to)101-126
Number of pages26
JournalStudies in Computational Intelligence
Volume43
DOIs
Publication statusPublished - 29 Jan 2007
Externally publishedYes

Fingerprint

Quality management
Information management
Data mining
Data structures
Cleaning

Keywords

  • Data cleaning
  • Data quality management
  • Data quality metadata
  • Record linkage

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Measuring and modelling data quality for quality-awareness in data mining. / Berti-Equille, Laure.

In: Studies in Computational Intelligence, Vol. 43, 29.01.2007, p. 101-126.

Research output: Contribution to journalArticle

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