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