Name
Abstract | ||
|---|---|---|
Motivated by the declarative modeling paradigm for data mining, we report on our experience in modeling and solving relational query and graph mining problems with the IDP system, a variation on the answer set programming paradigm. Using IDP or other ASPlanguages for modeling appears to be natural given that they provide rich logical languages for modeling and solving many search problems and that relational query mining (and ILP) is also based on logic. Nevertheless, our results indicate that second order extensions to these languages are necessary for expressing the model as well as for efficient solving, especially for what concerns subsumption testing. We propose such second order extensions and evaluate their potential effectiveness with a number of experiments in subsumption as well as in query mining. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-40566-7_12 | INDUCTIVE LOGIC PROGRAMMING, ILP 2015 |
Keywords | Field | DocType |
Knowledge representation, Answer set programming, Data mining, Query mining, Pattern mining | Graph,Knowledge representation and reasoning,Computer science,Theoretical computer science,Logic programming,Answer set programming | Conference |
Volume | ISSN | Citations |
9575 | 0302-9743 | 4 |
PageRank | References | Authors |
0.40 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergey Paramonov | 1 | 17 | 4.72 |
| Matthijs Van Leeuwen | 2 | 299 | 24.85 |
| Marc Denecker | 3 | 1626 | 106.40 |
| Luc De Raedt | 4 | 5481 | 505.49 |