Large scale skill matching through knowledge compilation

We present a logic-based framework for automated skill matching, able to return a ranked referral list and the related ranking explanation. Thanks to a Knowledge Compilation approach, a knowledge base in Description Logics is translated into a relational database, without loss of information. Skill matching inference services are then efficiently executed via SQL queries. Experimental results for scalability and turnaround times on large scale data sets are reported, confirming the validity of the approach.