WebLQM is a system with capabilities to locate, query and mine web communities on the Internet. WebLQM has a special way to define the World Wide Web, its contents and relations. ...
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Computing frequent itemsets is one of the most prominent problems in data mining. We study the following related problem, called FREQSAT, in depth: given some itemset-interval pai...
As the result of interactions between visitors and a web site, an http log file contains very rich knowledge about users on-site behaviors, which, if fully exploited, can better c...
The application of frequent patterns in classification has demonstrated its power in recent studies. It often adopts a two-step approach: frequent pattern (or classification rule) ...