Search

Writing study regulations for academic study programs and automatically implementing those regulations is a difficult task that involves a variety of actors and requires at each step careful compliance to the constraints defined in the regulations. This paper describes: (1) the innovation process, taking place through a hands-on experiment, that lead the R&D Unit of the University of Geneva to provide a proposal for a digital service targeting the above purpose; (2) the actual design of such a digital service, providing various functionalities: (a) the elaboration of study regulations; (b) the elaboration of the corresponding study plan; (c) the actual implementation of the study plan through the information system. The digital service relies on two main ideas: (1) all study regulations and study plans are built from common atomic elements, that we call building blocks; (2) ensuring compliance to various constraints is achieved through a reasoning engine capturing the constraints defined over an ontology of the study regulations domain. Each year, for a given University, several study regulations, with various constraints and structure are defined or updated. They all need to be carefully crafted and implemented. The work presented in this paper has the potential to alleviate and improve this task for the various actors involved (students, program directors, lawyers, scientific committee members, study advisor, information systems managers, students’ office).

Organisations heavily dependent on paper documents still spend a significant amount of time managing a large volume of documents. An intelligent document management system (DMS) is presented to automate the processing of tax and administrative documents. The proposed system fills a gap in the landscape of practical tools in the field of DMS and advances the state of the art. This system represents a complex process of integrated AI-powered technologies that creates an ontology, extracts information from documents, defines profiles, maps the extracted data in RDF format, and applies inference through a reasoning engine. The DMS was designed to help all those companies that manage their clients' tax and administrative documents daily. Automation speeds up the management process so that companies can focus more on value-added services. The system was tested in a case study that focused on the preparation of tax returns. The results demonstrated the efficacy of the system in providing document management service. [ABSTRACT FROM AUTHOR]