SeMatching: Using semantics to perform pair matching in mentoring processes

Abstract

The importance of the human factor in 21st century organizations means that the competent development of professionals has become a key aspect. In this environment, mentoring has emerged as a common and efficient practice for the development of knowledge workers. Following the surge of concepts such as eMentoring, advancements of the Internet and its evolution towards a Semantic Web, such developments present novel opportunities for the improvement of the different characteristics of mentoring. Basing itself on such advancements, this paper presents SeMatching, a semantics-based platform which utilizes different personal and professional information to carry out pair matching of mentors and mentees. © 2009 Springer Berlin Heidelberg.