We extend the problem of association rule mining – a key data mining problem – to systems in which the database is partitioned among a very large number of computers that are ...
Association Rules Mining (ARM) algorithms are designed to find sets of frequently occurring items in large databases. ARM applications have found their way into a variety of field...
In recent years interest has grown in “mining” large databases to extract novel and interesting information. Knowledge Discovery in Databases (KDD) has been recognised as an em...
We propose a framework, called MIC, which adopts an information-theoretic approach to address the problem of quantitative association rule mining. In our MIC framework, we first d...
Database integration of mining is becoming increasingly important with tile installation of larger and larger data warehouses built around relational database technology. Most of ...