Description
| Title | Learning Datalog Programs from Input and Output |
| Abstract | A new inductive learning task is proposed for Datalog programs. In the learning task an example is a pair hI;Oi where I and O, standing for input and output respectively, are sets of ground atoms. It means that O is the least (Herbrand) model of a learned Datalog program when it is given the input I. An inductive learning algorithm is presented for this inductive learning task. It is a modular and anytime algorithm. |
Other presentations by Xu Wang
| Date | Title |
|---|---|
| 18 December 2017 | Learning Datalog Programs from Input and Output |
| 09 December 2019 | Could we reduce domain classification for datasets to ontology classification for datasets? |