With the large number of projects at EU, Work Package 8 in the ENLIVEN project establishes the theory to build an Intelligent Decision Support System (IDSS) to support evidence-based policy learning. It has been found that most of the existing documentations have been archived in scattered places, quite often in different formats, and with different levels of details. This inconsistent documentation presents a challenge for extracting the rich knowledge in practice to build a coherent intelligent system for sharing expertise in policy making across EU countries.
A unified template of 78 attributes has therefore been established for storing projects for young people Not in Education, Employment and Training (NEET) in a consistent format in the knowledge base. With this template, previous projects in the knowledge base can be measured against four key attributes (aims, activities, target groups and regions), and those in similar scenarios can be retrieved to support policy learning and decision making. The research also demonstrates the use of machine learning techniques in Artificial Intelligence to automatically extract and identify the barriers of young people to employment in a case study on TalentMatch, a UK project with sufficient participants details.