Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workfor...
Commercial relational databases currently store vast amounts of real-world data. The data within these relational repositories are represented by multiple relations, which are int...
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Discovering sequential patterns is an important problem in data mining with a host of application domains including medicine, telecommunications, and the World Wide Web. Conventio...
Minos N. Garofalakis, Rajeev Rastogi, Kyuseok Shim