PRODIMA: PRObabilistic Data and information Integration with provenance MAnagement
The PRODIMA project investigates provenance-based probabilistic information integration in the Semantic Web. The research hypothesis is that provenance improves probabilistic information integration in the Web, i.e., speeds up probabilistic reasoning and facilitates (probabilistic) mapping debugging at the same time. The following four research objectives have been stated around the above research hypothesis: (i) investigation of the notion of provenance and uncertain provenance in probabilistic information integration frameworks and definition of its requirements and properties; (ii) investigation of probabilistic logics capable for realizing probabilistic information integration as a possible host logical formalism for representing uncertain provenance; (iii) investigation of the impact of (uncertain) provenance on the reasoning process and on mapping debugging within a probabilistic information integration framework; and (iv) elaboration and investigation of scalable reasoning algorithms that incorporate the collection and storage of provenance information and facilitate the debugging of probabilistic mappings.
Selected Publications
-
Ranking Answers to Datalog+⁄− Ontologies based on Trust and Reliability of Subjective Reports
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Cristian Molinaro‚ Livia Predoiu and Gerardo I. Simari
In Christoph Beierle‚ Gerhard Brewka and Matthias Thimm:, editors, Computational Models of Rationality: Essays Dedicated to Gabriele Kern−Isberner on the Occasion of Her 60th Birthday. Vol. 29 of Tributes. Pages 175−192. College Publications. January, 2016.
Details about Ranking Answers to Datalog+⁄− Ontologies based on Trust and Reliability of Subjective Reports | BibTeX data for Ranking Answers to Datalog+⁄− Ontologies based on Trust and Reliability of Subjective Reports
-
Generalized Consistent Query Answering under Existential Rules
Thomas Eiter‚ Thomas Lukasiewicz and Livia Predoiu
In James P. Delgrande and Frank Wolter, editors, Proceedings of the 15th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2016‚ Cape Town‚ South Africa‚ April 25−29‚ 2016. Pages 359−368. AAAI Press. April, 2016.
Details about Generalized Consistent Query Answering under Existential Rules | BibTeX data for Generalized Consistent Query Answering under Existential Rules | Link to Generalized Consistent Query Answering under Existential Rules
-
Basic Probabilistic Ontological Data Exchange with Existential Rules
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Livia Predoiu and Gerardo I. Simari
In Dale Schuurmans and Michael Wellman, editors, Proceedings of the 30th National Conference on Artificial Intelligence‚ AAAI 2016‚ Phoenix‚ Arizona‚ USA‚ February 12–17‚ 2016. Pages 1023−1029. AAAI Press. February, 2016.
Details about Basic Probabilistic Ontological Data Exchange with Existential Rules | BibTeX data for Basic Probabilistic Ontological Data Exchange with Existential Rules | Link to Basic Probabilistic Ontological Data Exchange with Existential Rules
Principal Investigator
People
Share this:
