Making Business Partner Recommendation More Effective: Impacts of Combining Recommenders and Explanations through User Feedback

Abstract

Business partnerships can help businesses deliver on opportunities they might otherwise be unable to facilitate. Finding the right business partner (BP) involves understanding the needs of the businesses along with what they can deliver in a collaboration. BP recommendation meets this need by facilitating the process of finding the right collaborators to initiate a partnership. In this paper, we present a real world BP recommender application which uses a similarity based technique to generate and explain BP suggestions, and we discuss how this application is enhanced by integrating a solution that 1. dynamically combines different recommender algorithms, and 2. enhances the explanations to the recommendations, in order to improve the user's experience with the tool. We conducted a preliminary focus group study with domain experts which supports the validity of the enhancements achieved by integrating our solution and motivates further research directions.