The Need for Identifying Ways to Monetize Personalization and Recommendation.

ADJUNCT PUBLICATION OF THE 27TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (ACM UMAP '19 ADJUNCT)(2019)

引用 2|浏览13
暂无评分
摘要
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.
更多
查看译文
关键词
multi-sided recommender systems,fair recommender systems,commercial applications,academic research
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要