A probabilistic model for data cube compression and query approximation
Rokia Missaoui, Cyril Goutte, Anicet Kouomou Choupo, Ameur Boujenoui · 2007
Databases and data warehouses contain an overwhelming volume of information that users must wade through in order to extract valuable and actionable knowledge to supportthe decision-making process. This contribution addresses the problem of automatically analyzing large multidimensional tables to get a concise representation of data, identify patterns and provide approximate answers to queries.