Name
Title | ||
|---|---|---|
Mining Association Rules with Respect to Support and Anti-support-Experimental Results |
Abstract | ||
|---|---|---|
Evaluating the interestingness of rules or trees is a challenging problem of knowledge discovery and data mining. In recent studies, the use of two interestingness measures at the same time was prevailing. Mining of Pareto-optimal borders according to support and confidence, or support and anti-support are examples of that approach. Here, we consider induction of "if..., then..." association rules with a fixed conclusion. We investigate ways to limit the set of rules non---dominated wrt support and confidence or support and anti-support, to a subset of truly interesting rules. Analytically, and through experiments, we show that both of the considered sets can be easily reduced by using the valuable semantics of confirmation measures. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-73451-2_56 | RSEISP |
Keywords | Field | DocType |
data mining,confirmation measure,pareto-optimal border,interesting rule,rules non,mining association rules,fixed conclusion,challenging problem,association rule,interestingness measure,wrt support,anti-support-experimental results | Association rule learning,Knowledge extraction,Artificial intelligence,Machine learning,Semantics,Mathematics | Conference |
Volume | ISSN | Citations |
4585 | 0302-9743 | 5 |
PageRank | References | Authors |
0.56 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roman Slowinski | 1 | 5561 | 516.06 |
| Izabela Szczęch | 2 | 56 | 7.90 |
| Mirosław Urbanowicz | 3 | 5 | 0.56 |
| Salvatore Greco | 4 | 3977 | 266.79 |