Ricerc@Sapienza

We present an approach based on GATE (General Architecture for Text Engineering) for the automatic population of ontologies from text documents. We describe some experimental results, which are encouraging in terms of extracted correct instances of the ontology. We then focus on a phase of our pipeline and discuss a variant thereof, which aims at reducing the manual effort needed to generate pre-defined dictionaries used in document annotation. Our additional experiments show promising results also in this case.

In Controlled Query Evaluation (CQE) confidential data are protected through a declarative policy and a (optimal) censor, which guarantees that answers to queries are maximized without disclosing secrets. In this paper we consider CQE over Description Logic ontologies and study query answering over all optimal censors. We establish data complexity of the problem for ontologies specified in DL-LiteR and for variants of the censor language, which is the language used by the censor to enforce the policy.

We study the problem of designing reverse engineering techniques for associating semantic descriptions to existing data services. We base our proposal on the Ontology-Based Data Access paradigm, where a domain ontology is used to provide a semantic layer mapped to the data sources of an organization. The basic idea is to perform the reverse engineering of a data service, expressed a query over the data sources, by deriving a query over the ontology that explains the semantics of the data service in terms of the element of the ontology.