In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
When applying association mining to real datasets, a major obstacle is that often a huge number of rules are generated even with very reasonable support and confidence. Among thes...
Ping Chen, Rakesh M. Verma, Janet C. Meininger, We...
Associative classification is a promising classification approach that utilises association rule mining to construct accurate classification models. In this paper, we investigate ...
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...
: Sufficiently high data quality is crucial for almost every application. Nonetheless, data quality issues are nearly omnipresent. The reasons for poor quality cannot simply be bla...