"Bee and I need diversity!" Break Filter Bubbles in Recommendation Systems through Embodied AI Learning-Reference-Cited by-同舟云学术

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"Bee and I need diversity!" Break Filter Bubbles in Recommendation Systems through Embodied AI Learning

Published:2024-06-17 Issue: Volume:11 Page:44-61
ISSN:
Container-title:Proceedings of the 23rd Annual ACM Interaction Design and Children Conference
language:
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Author:

Zhou Xiaofei¹^ORCID,Zhou Yushan¹^ORCID,Gong Yunfan²^ORCID,Cai Zhenyao³^ORCID,Qiu Annie⁴^ORCID,Xiao Qinqin²^ORCID,Antle Alissa N.⁵^ORCID,Bai Zhen¹^ORCID

Affiliation:

1. Department of Computer Science, University of Rochester, United States

2. Warner School of Education, University of Rochester, United States

3. School of Education, University of California Irvine, United States

4. Computer Science, University of Rochester, United States

5. School of Interactive Arts and Technology, Simon Fraser University, Canada

Funder

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3628516.3655802

Reference127 articles.

1. Data Mining: Data Mining Concepts and Techniques

2. Charu C Aggarwal. 2016. Content-Based Recommender Systems. In Recommender Systems: The Textbook, Charu C Aggarwal (Ed.). Springer International Publishing, Cham, 139–166.

3. Safinah Ali, Blakeley H Payne, Randi Williams, Hae Won Park, and Cynthia Breazeal. 2019. Constructionism, ethics, and creativity: Developing primary and middle school artificial intelligence education. In International workshop on education in artificial intelligence k-12 (eduai’19), Vol. 2. 1–4.

4. Maxine Alterio and Janice McDrury. 2003. Learning through storytelling in higher education: Using reflection and experience to improve learning. Routledge.

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