论文标题
为什么我不跟随你？负责任的推荐系统的原因和原因
Why should I not follow you? Reasons For and Reasons Against in Responsible Recommender Systems
论文作者
论文摘要
一些推荐系统（RS）诉诸于解释，以增强对建议的信任。但是，当前的解释生成技术倾向于强烈维护推荐的产品，而不是提出既有原因又是针对它们的原因。我们认为，RS可以通过坦率地向用户展示两种原因来更好地提高整体信任和透明度。我们通过利用知识图和应用SNEDEGAR的实用推理理论来开发这种RS。我们表明，我们的实施RS具有出色的性能，我们对人类受试者进行了一项实验，该实验表明了同时提出和反对的原因，并在信任，参与和说服力方面有了重大改善。
A few Recommender Systems (RS) resort to explanations so as to enhance trust in recommendations. However, current techniques for explanation generation tend to strongly uphold the recommended products instead of presenting both reasons for and reasons against them. We argue that an RS can better enhance overall trust and transparency by frankly displaying both kinds of reasons to users.We have developed such an RS by exploiting knowledge graphs and by applying Snedegar's theory of practical reasoning. We show that our implemented RS has excellent performance and we report on an experiment with human subjects that shows the value of presenting both reasons for and against, with significant improvements in trust, engagement, and persuasion.
