Technical and Procedural Knowledge Extraction with Question Answering

Engineering organisations like Thales rely on large quantities of technical knowledge. When resolving a technical problem, for example, users have to follow a multi-step procedure in which the steps are described with various levels of detail, may not be up to date, or may not target the exact problem they are facing. In this context, our project aims at developing AI language and knowledge representation models that will represent technical knowledge from an unstructured dataset of procedures, in order to identify missing knowledge through a question-answering process. By integrating such models with our knowledge management solutions, we expect to identify procedures that need to be improved, the specific information that needs improvement, and which information or person in the organisation could provide this improvement.

Faculty Supervisor:

Bang Liu

Student:

Partner:

Thales Canada Inc (Montreal, QC)

Discipline:

Computer science

Sector:

Management of companies and enterprises; Manufacturing; Professional, scientific and technical services

University:

Université de Montréal

Program: