Link key extraction with relational concept analysis

Participants : Manuel Atencia, Jérôme David [Correspondent] , Jérôme Euzenat.

Link key extraction under ontological constraints

Participants : Jérôme David [Correspondent] , Jérôme Euzenat, Khadija Jradeh.

We investigated the use of link keys taking advantage of ontologies. This can be carried out in two different directions: exploiting the ontologies under which data sets are published, and extracting link keys using ontology constructors for combining attribute and class names.

Following the first approach, we extended our existing algorithms to extract link keys involving inverse (${}^{-1}$), union ($\bigsqcup$), intersection ($\sqcap$) and paths ($\circ$) of properties. This helps providing link keys when it is not possible otherwise (without inverse, there is no possible correspondence if one data set is using parents and the other is using children). We showed how the paths could be normalised to reduce the search space. Extracting link keys under these conditions required to introduce better indexing techniques to avoid unnecessary link key generation and even looping.

We implemented this method and evaluated it by running experiments on two real data sets, this resulted in finding the correct link keys that were not found without them.

Tableau method for $\mathrm{𝒜ℒ𝒞}+$Link key reasoning

Participants : Manuel Atencia [Correspondent] , Jérôme Euzenat, Khadija Jradeh.

Link keys can also be thought of as axioms in a description logic. We further worked on the tableau method designed for the $\mathrm{𝒜ℒ𝒞}$ description logic to support reasoning with link keys.