User Control in Recommender Systems: Overview and Interaction Challenges
User Control in Recommender Systems: Overview and Interaction Challenges
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推荐系统中的用户控制：概述和交互挑战
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Michael Jugovac
中科院分区：
文献类型：
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作者：
D. Jannach;Sidra Naveed;Michael Jugovac
推荐系统已被证明是有价值的工具，可以帮助用户在信息过载的情况下找到感兴趣的项目。这些系统通常根据用户过去的偏好和观察到的行为来预测每个项目与个人用户的相关性。然而，如果系统关于用户偏好的假设是不正确的或过时的，则应提供使用户控制推荐的机制，例如，让他们明确地指定自己的偏好，或者允许他们对建议提供反馈。在本文中，我们对研究文献中让用户主动控制推荐内容的不同方法进行了回顾和分类。我们强调了相应的用户交互机制的设计相关的挑战，最后提出了一个基于调查的研究，我们收集了用户反馈的亚马逊上实现的用户控制功能的结果。
Recommender systems have shown to be valuable tools that help users find items of interest in situations of information overload. These systems usually predict the relevance of each item for the individual user based on their past preferences and their observed behavior. If the system’s assumption about the users’ preferences are however incorrect or outdated, mechanisms should be provided that put the user into control of the recommendations, e.g., by letting them specify their preferences explicitly or by allowing them to give feedback on the recommendations. In this paper we review and classify the different approaches from the research literature of putting the users into active control of what is recommended. We highlight the challenges related to the design of the corresponding user interaction mechanisms and finally present the results of a survey-based study in which we gathered user feedback on the implemented user control features on Amazon.