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Author DUrso, Ciro
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2016
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Data quality process ♦ Data preparation for econometrics of public policy evaluation ♦ Databases ♦ Outlier identification
Abstract Enterprise's archives are inevitably affected by the presence of data quality problems (also called glitches). This article proposes the application of a new method to analyze the quality of datasets stored in the tables of a database, with no knowledge of the semantics of the data and without the need to define repositories of rules. The proposed method is based on proper revisions of different approaches for outlier detection that are combined to boost overall performance and accuracy. A novel transformation algorithm is conceived that treats the items in database tables as data points in real coordinate space of $\textit{n}$ dimensions, so that fields containing dates and fields containing text are processed to calculate distances between those data points. The implementation of an iterative approach ensures that global and local outliers are discovered even if they are subject, primarily in datasets with multiple outliers or clusters of outliers, to masking and swamping effects. The application of the method to a set of archives, some of which have been studied extensively in the literature, provides very promising experimental results and outperforms the application of a single other technique. Finally, a list of future research directions is highlighted.
Description Author Affiliation: Lumsa University/Italian Senate, Rome (DUrso, Ciro)
ISSN 19361955
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2016-09-01
Publisher Place New York
e-ISSN 19361963
Journal Journal of Data and Information Quality (JDIQ)
Volume Number 7
Issue Number 3
Page Count 22
Starting Page 1
Ending Page 22

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Source: ACM Digital Library