The 1st Workshop on Human-Centered Recommender Systems

• URL: http://arxiv.org/abs/2411.14760v1
• Date: Fri, 22 Nov 2024 06:46:41 GMT
• Title: The 1st Workshop on Human-Centered Recommender Systems
• Authors: Kaike Zhang, Yunfan Wu, Yougang lyu, Du Su, Yingqiang Ge, Shuchang Liu, Qi Cao, Zhaochun Ren, Fei Sun,
• Abstract summary: This workshop aims to provide a platform for researchers to explore the development of Human-Centered Recommender Systems. HCRS refers to the creation of recommender systems that prioritize human needs, values, and capabilities at the core of their design and operation. In this workshop, topics will include, but are not limited to, robustness, privacy, transparency, fairness, diversity, accountability, ethical considerations, and user-friendly design.
• Score: 27.23807230278776
• License:
• Abstract: Recommender systems are quintessential applications of human-computer interaction. Widely utilized in daily life, they offer significant convenience but also present numerous challenges, such as the information cocoon effect, privacy concerns, fairness issues, and more. Consequently, this workshop aims to provide a platform for researchers to explore the development of Human-Centered Recommender Systems~(HCRS). HCRS refers to the creation of recommender systems that prioritize human needs, values, and capabilities at the core of their design and operation. In this workshop, topics will include, but are not limited to, robustness, privacy, transparency, fairness, diversity, accountability, ethical considerations, and user-friendly design. We hope to engage in discussions on how to implement and enhance these properties in recommender systems. Additionally, participants will explore diverse evaluation methods, including innovative metrics that capture user satisfaction and trust. This workshop seeks to foster a collaborative environment for researchers to share insights and advance the field toward more ethical, user-centric, and socially responsible recommender systems.

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