Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Algorithms for finding frequent itemsets fall into two broad classes: (1) algorithms that are based on non-trivial SQL statements to query and update a database, and (2) algorithms...
Multi-core processors are proliferated across different domains in recent years. In this paper, we study the performance of frequent pattern mining on a modern multi-core machine....
Abstract In recent years, researchers have begun to study inductive databases, a new generation of databases for leveraging decision support applications. In this context, the user...
Condensed representations of pattern collections have been recognized to be important building blocks of inductive databases, a promising theoretical framework for data mining, and...