A learning feature engineering method for task assignment

Abstract

Multi-domain IT services are delivered by technicians with a variety of expert knowledge in different areas. Their skills and availability are an important property of the service. However, most organizations do not have a consistent view of this information because creation and maintenance of a skill model is a difficult task, especially in light of privacy regulations, changing service catalogs and worker turnover. We propose a method for ranking technicians on their expected performance according to their suitability for receiving the assignment of a service request without maintaining an explicit skill model describing which skills are possessed by each technician. We find appropriate assignees by making use of similarities between the assignees and previous tasks performed by them. © 2012 IEEE.