Name
Abstract | ||
|---|---|---|
Association rule mining is a technique widely used in the field of data mining, which consists in discovering relationships and/or correlations between the attributes of a database. However, the method brings known problems among which the fact that a large number of association rules may be extracted, not all of them being relevant or interesting for the domain expert. In that context, we propose a practical, interactive and helpful guided approach to visualize, evaluate and compare the extracted rules following a step by step methodology, taking into account the interaction between the industrial domain expert and the data mining expert. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-662-44739-0_12 | ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: INNOVATIVE AND KNOWLEDGE-BASED PRODUCTION MANAGEMENT IN A GLOBAL-LOCAL WORLD, PT 1 |
Keywords | Field | DocType |
Knowledge Discovery from Databases,Association Rules Mining,Post-processing phase,Interactivity,Decision Support System | Interactivity,Data mining,Subject-matter expert,Computer science,Decision support system,Association rule learning | Conference |
Volume | ISSN | Citations |
438 | 1868-4238 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paula Andrea Potes Ruiz | 1 | 50 | 2.02 |
| Bernard Kamsu-Foguem | 2 | 318 | 20.94 |
| B. Grabot | 3 | 210 | 20.58 |