HELP: A Recommender System to Locate Expertise in Organizational Memories

The rapid evolution of our world means that learning and knowledge sharing are fast becoming a key challenge for individuals and organizations. In this paper, we present a system called HELP, whose aim is to locate information and recommend experts in organizations. Each user is being viewed simultaneously as an expert and a learner. We use two approaches: The first one consists of making the system retrieve one or several requests similar to the seeking-learner´s request using a textual case-based reasoning technique. The second approach aims at locating experts in specific areas in order to recommend them to the users who request this expertise. For this purpose, we use a hybrid recommendation technique based on Collaborative Filtering (CF) and Case-Based Reasoning (CBR). In contrast to existing approaches in expertise location, we believe that CBR combined to CF enables HELP to better recommend expertise, taking into account the user´s feedback concerning the technical and pedagogical skills of the experts.