Approches combinées pour raisonnements et requêtes expressives sur des données massives // Approches combinées pour raisonnements et requêtes expressives sur des données massives

Approches combinées pour raisonnements et requêtes expressives sur des données massives
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Combined approaches for scalable reasoning on rich queries

Negation and aggregation are key features for deeply impactful data-analysis. Yet, it is well known that when equipping declarative rule- languages with such features reasoning becomes infeasible. In this thesis, we are focusing on the development of novel algorithms for rich queries based on existential rules [1], including such features, but by focusing our attention on practically relevant fragments of rules including negation (starting from semi-positive rules) and aggregation, which are known to ensure decidability and tractability. The originality of our work will consist in the study of combined-approaches leveraging on query-rewriting and materialisation techniques which will pave the way to scalable reasoning on top of existing database technology. Any implementations will be included in the InteGraal library (gitlab.inria.fr/rules/integraal).
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Début de la thèse : 01/10/2025

Public funding alone (i.e. government, region, European, international organization research grant)

Concours pour un contrat doctoral

Université de Montpellier

166 I2S - Information, Structures, Systèmes

Compétences solides en logique et bases de données. Plus : théorie de la complexité / développement logiciel.
Solid skill in logics and databases. Plus : complexity theory / software development.