The Need for Identifying Ways to Monetize Personalization and Recommendation

Abstract

Research on user modeling and personalization typically only serves the needs of end-users. However, when applied in real-world, commercial contexts, recommendations should also serve the (often monetary) interests of other parties, such as platform providers, sellers and advertisers. This paper provides a brief historical perspective on the research field, contrasts this with the commercial context, and investigates the topics currently addressed at the UMAP and RecSys conferences. The paper concludes with a discussion on the need for the research community to take multi-stakeholder interests into account in the design and evaluation of adaptive systems. This would allow us to foresee unwanted effects, such as online filter bubbles, and to pro-actively find strategies to prevent them.