Developing an Ontology-Based Team Recommender System using EDON Method

Abstract

Recently, Team Recommender Systems (TRS) have become ex-tremely common because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest infor-mation. In recent years, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. Despite of the advance done, building methodologies for developing ontology-based systems is still a research area. In this paper, we report our experience in developing an ontology-based TRS by using the EDON method. The developed TRS analyses human resource information to recom-mend a work team for a software development project.