Name
Abstract | ||
|---|---|---|
We present a prototype of an inductive database. Our system enables the user to query not only the data stored in the database but also generalizations (e.g. rules or trees) over these data through the use of virtual mining views. The mining views are relational tables that virtually contain the complete output of data mining algorithms executed over a given dataset. The prototype implemented into PostgreSQL currently integrates frequent itemset, association rule and decision tree mining. We illustrate the interactive and iterative capabilities of our system with a description of a complete data mining scenario. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1401890.1402019 | KDD |
Keywords | Field | DocType |
inductive database prototype,frequent itemset,data mining,complete output,virtual mining view,inductive database,complete data mining scenario,association rule,mining view,iterative capability,decision tree mining,decision tree | Decision tree,Data mining,Data stream mining,Concept mining,Generalization,Computer science,View,Database design,Association rule learning,Decision tree learning,Database | Conference |
Citations | PageRank | References |
8 | 0.55 | 8 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hendrik Blockeel | 1 | 2744 | 177.48 |
| Toon Calders | 2 | 1333 | 93.66 |
| Élisa Fromont | 3 | 192 | 25.51 |
| Bart Goethals | 4 | 1575 | 94.55 |
| Adriana Prado | 5 | 87 | 5.14 |
| Céline Robardet | 6 | 696 | 60.36 |