PT Unknown
AU Sivogolov, E
TI Evaluation of Impact of Data Quality on Clustering with Syntactic Cluster Validity Methods
SE Bericht des Instituts für Informatik
PY 1992
VL 1107
PU Institut für Informatik
WP https://macau.uni-kiel.de/receive/macau_mods_00001814
LA en
SN 2192-6247
AB In this research the influence of four most commonly used data quality dimensions (accuracy, completeness, consistency and timeliness) on clustering outcomes was studied. Statistical significant negative effect of low data quality levels on results of different clustering algorithms was demonstrated. The relationship between Data Quality concepts and clustering concepts were constructed and some recommendations on usage of clustering algorithms with respect to data quality level were made.
PI Kiel
ER