References

An AI-powered intelligent document management system (DMS) is introduced to automate the processing of tax and administrative documents, enhancing efficiency and allowing companies to focus on value-added services.

This report covers the RAR project, which automates updating the underground cadastre for water, gas, and heating networks using AI and semantic reasoning.

This poster was presented at the poster session of The Knowledge Graph Conference. New York City, NY

A method for automatically generating a service compliant with study regulations, offering personalized views for various university actors, demonstrated through a PhD student case study.

A semantic rule-based RDF DMS using ontology and SHACL to enhance document management by reasoning on legal regulations and user profiles.

A semantic rule-based approach to enhance DMSs by automating document classification, reasoning, and profiling, demonstrated with a Swiss tax case study.

This project automates the processing of Swiss tax documents using AI to help companies profile clients and make better decisions.

A model for representing subsurface geometries in knowledge graphs, addressing uncertainty and time variation with OWL ontology and RDF-star.