TastePaths: Enabling Deeper Exploration and Understanding of Personal Preferences in Recommender Systems

Author:

Petridis Savvas1,Daskalova Nediyana2,Mennicken Sarah2,Way Samuel F2,Lamere Paul2,Thom Jennifer2

Affiliation:

1. Computer Science Department, Columbia University, United States

2. Spotify, United States

Publisher

ACM

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles;Proceedings of the 29th International Conference on Intelligent User Interfaces;2024-03-18

2. Exploring Categorizations of Algorithmic Affordances in Graphical User Interfaces of Recommender Systems;Lecture Notes in Computer Science;2024

3. Looking at the FAccTs: Exploring Music Industry Professionals' Perspectives on Music Streaming Services and Recommendations;Proceedings of the 2nd International Conference of the ACM Greek SIGCHI Chapter;2023-09-27

4. How applicable are attribute-based approaches for human-centered ranking creation?;Computers & Graphics;2023-08

5. 2 User-centered recommender systems;Personalized Human-Computer Interaction;2023-07-24

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