— One of the central problems for data quality is inconsistency detection. Given a database D and a set Σ of dependencies as data quality rules, we want to identify tuples in D ...
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Despite advances in the application of automated statistical and machine learning techniques to system log and trace data there will always be a need for human analysis of machine...
s of the LIX Fall Colloquium 2008: Emerging Trends in Visual Computing Frank Nielsen Ecole Polytechnique, Palaiseau, France Sony CSL, Tokyo, Japan Abstract. We list the abstracts o...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...