Abstract. We consider a problem that is related to the “Universal Encoding Problem” from information theory. The basic goal is to find rules that map “partial information”...
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...
In this paper we propose an adaptive local pruning method for association rules. Our method exploits the exact mapping between a certain class of association rules, namely those w...
Frequent association rules (e.g., AB C to say that when properties A and B are true in a record then, C tends to be also true) have become a popular way to summarize huge datasets...
We define an optimal class association rule set to be the minimum rule set with the same predictive power of the complete class association rule set. Using this rule set instead o...