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Multistakeholder recommendation: Survey and research directions

机译：多方利益相关者建议：调查和研究方向

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摘要

Recommender systems provide personalized information access to users of Internet services from social networks to e-commerce to media and entertainment. As is appropriate for research in a field with a focus on personalization, academic studies of recommender systems have largely concentrated on optimizing for user experience when designing, implementing and evaluating their algorithms and systems. However, this concentration on the user has meant that the field has lacked a systematic exploration of other aspects of recommender system outcomes. A user-centric approach limits the ability to incorporate system objectives, such as fairness, balance, and profitability, and obscures concerns that might come from other stakeholders, such as the providers or sellers of items being recommended. Multistakeholder recommendation has emerged as a unifying framework for describing and understanding recommendation settings where the end user is not the sole focus. This article outlines the multistakeholder perspective on recommendation, highlighting example research areas and discussing important issues, open questions, and prospective research directions.
机译：推荐系统为Internet服务的用户提供个性化的信息访问，这些用户从社交网络到电子商务再到媒体和娱乐。对于适合于个性化领域的研究而言，推荐系统的学术研究主要集中在优化设计，实现和评估其算法和系统时的用户体验。但是，这种对用户的关注意味着该领域缺乏对推荐系统结果其他方面的系统研究。以用户为中心的方法限制了合并诸如公平性，平衡性和盈利性之类的系统目标的能力，并掩盖了可能来自其他利益相关者（例如所推荐项目的提供者或销售者）的担忧。多利益相关方推荐已成为描述和理解推荐设置的统一框架，而最终用户并不是唯一的关注点。本文概述了多方利益相关者对推荐的观点，突出了示例研究领域，并讨论了重要问题，未解决的问题和前瞻性研究方向。

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