Section: New Results
Linking Data Graphs
Angela Bonifati, Radu Ciucanu, Slawomir Staworko developed techniques to learn conjunctive queries from example given by a user. The main part is to infer joins between relations from the positive and negative tuples. Different techniques to deduce informative examples are presented and interestingly they can be done in polynomial time. The techniques are published in  and demonstrated in  .
Grégoire Laurence, Aurélien Lemay, Joachim Niehren, Slawek Staworko, Marc Tommasi  explain how to learn sequential top-down tree-to- word transducers (STWs). First, they present a Myhill-Nerode characterization of the corresponding class of sequential tree-to-word transformations (STW). Next, they investigate what learning of stws means, identify fundamental obstacles, and propose a learning model with abstain. Finally, they present a polynomial learning algorithm