论文标题
值得信赖的推荐系统
Trustworthy Recommender Systems
论文作者
论文摘要
推荐系统（RSS）旨在帮助用户从大型目录中有效检索其兴趣的项目。在很长一段时间内，研究人员和从业人员一直专注于开发准确的RSS。近年来，来自攻击，系统和用户产生的噪音，系统偏见的RSS威胁越来越多。结果，很明显，严格关注RS准确性是有限的，研究必须考虑其他重要因素，例如值得信赖。对于最终用户而言，值得信赖的RS（TRS）不仅应该是准确的，而且应该是透明，无偏见，公平的，并且对噪音或攻击也有牢固。这些观察实际上导致了RSS研究的范式转移：从面向准确的RSS到TRS。但是，研究人员缺乏对这个小说和快速发展的TRS领域的文献进行系统的概述和讨论。为此，在本文中，我们提供了TRS的概述，包括讨论TRS的动机和基本概念，对构建TRS的挑战的介绍以及该领域未来方向的观点。我们还提供了一个新颖的概念框架来支持TRS的构建。
Recommender systems (RSs) aim to help users to effectively retrieve items of their interests from a large catalogue. For a quite long period of time, researchers and practitioners have been focusing on developing accurate RSs. Recent years have witnessed an increasing number of threats to RSs, coming from attacks, system and user generated noise, system bias. As a result, it has become clear that a strict focus on RS accuracy is limited and the research must consider other important factors, e.g., trustworthiness. For end users, a trustworthy RS (TRS) should not only be accurate, but also transparent, unbiased and fair as well as robust to noise or attacks. These observations actually led to a paradigm shift of the research on RSs: from accuracy-oriented RSs to TRSs. However, researchers lack a systematic overview and discussion of the literature in this novel and fast developing field of TRSs. To this end, in this paper, we provide an overview of TRSs, including a discussion of the motivation and basic concepts of TRSs, a presentation of the challenges in building TRSs, and a perspective on the future directions in this area. We also provide a novel conceptual framework to support the construction of TRSs.
