Name
Abstract | ||
|---|---|---|
Association rules in data mining are considered from a point of view of conditional logic and rough sets. In our previous work, given an association rule in some fixed database, its corresponding Kripke model was formulated. Then, two difficulties in the formulation were pointed out: limitation of the form of association rules and limited formulation of the models themselves. To resolve the defects, Chellas's conditional logic was introduced and thereby, the class of conditionals in conditional logic can be naturally regarded as containing the original association rules. In this paper, further, an extension of conditional logic is introduced for dealing with association rules with intermediate values of confidence based on the idea of fuzzy-measure-based graded modal logic. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/3-540-45548-5_52 | JSAI Workshops |
Keywords | Field | DocType |
data mining,fuzzy-measure-based graded modal logic,conditional logic,intermediate value,association rules,fixed database,original association rule,corresponding kripke model,association rule,previous work,limited formulation,modal logic,rough set | Strict conditional,Discrete mathematics,Logical connective,Computer science,Multimodal logic,Substructural logic,Theoretical computer science,Artificial intelligence,Many-valued logic,Predicate logic,Intermediate logic,Higher-order logic | Conference |
ISBN | Citations | PageRank |
3-540-43070-9 | 2 | 0.61 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tetsuya Murai | 1 | 186 | 42.10 |
| Michinori Nakata | 2 | 292 | 37.49 |
| Yoshiharu Sato | 3 | 13 | 4.06 |