Article

Adaptive radio: achieving consensus using negative preferences

Authors:

Dennis L. Chao,

Justin Balthrop,

Stephanie ForrestAuthors Info & Claims

GROUP '05: Proceedings of the 2005 ACM International Conference on Supporting Group Work

Pages 120 - 123

https://doi.org/10.1145/1099203.1099224

Published: 06 November 2005 Publication History

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Abstract

We introduce the use of negative preferences to produce solutions that are acceptable to a group of users. This technique takes advantage of the fact that discovering what a user does not like can be easier than discovering what the user does like. To illustrate the approach, we implemented Adaptive Radio, a system that selects music to play in a shared environment. Rather than attempting to play the songs that users want to hear, the system avoids playing songs that they do not want to hear. Negative preferences could potentially be applied to information filtering, intelligent environments, and collaborative design.

References

[1]

Beersma, B. and De Dreu, C. K. W. Integrative and distributive negotiation in small groups: Effects of task structure, decision rule, and social motive. Organizational Behavior and Human Decision Processes, 87 (2002), 227--252.

Crossref

Google Scholar

[2]

Chao, D. L. and Forrest, S. Generating biomorphs with an aesthetic immune system. In R. Standish, M. A. Bedau, and H. A. Abbass, eds., Artificial Life VIII: Proceedings of the Eighth International Conference on the Simulation and Synthesis of Living Systems. MIT Press, Cambridge, Massachusetts, 2003, 89--92.

Digital Library

Google Scholar

[3]

Chao, D. L. and Forrest, S. Information immune systems. Genetic Programming and Evolvable Machines, 4, 4 (2003), 311--331.

Digital Library

Google Scholar

[4]

Deutsch, M. and Gerard, H. B. A study of normative and informational social influence upon social judgment. Journal of Abnormal and Social Psychology, 51 (1965), 629--636.

Crossref

Google Scholar

[5]

Goldberg, D., Nichols, D., Oki, B. M., and Terry, D. Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35, 12 (1992), 61--70.

Digital Library

Google Scholar

[6]

McCarthy, J. F. and Anagnost, T. D. MusicFX: An arbiter of group preferences for computer supported collaborative workouts. In Proceedings of the ACM 1998 Conference on Computer Supported Cooperative Work. ACM Press, New York, 1998, 363--372.

Digital Library

Google Scholar

[7]

McCarthy, J. F., Costa, T. J., and Liongosari, E. S. UniCast, OutCast & GroupCast: An exploration of new interaction paradigms for ubiquitous, peripheral displays. In Workshop on Distributed and Disappearing User Interfaces in Ubiquitous Computing at the SIGCHI Conference on Human Factors in Computer Systems (CHI 2001). ACM Press, New York, 2001.

Digital Library

Google Scholar

[8]

Moscovici, S. Towards a theory of conversion behavior. In L. Berkowitz, ed., Advances in experimental social psychology, Academic Press, London, 1980. 209--239.

Google Scholar

[9]

O'Connor, M., Cosley, D., Konstan, J. A., and Riedl, J. PolyLens: A recommender system for groups of users. In Proceedings of the Seventh European Conference on Computer Supported Cooperative Work. Kluwer Academic, New York, 2001, 199--218.

Digital Library

Google Scholar

Cited By

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Gabbolini GBridge D(2024)Surveying More Than Two Decades of Music Information Retrieval Research on PlaylistsACM Transactions on Intelligent Systems and Technology10.1145/368839815:6(1-68)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3688398
Gray RVillareale JFox TDallal DOntanon SArigo DJabbari SZhu J(2023)Improving Fairness in Adaptive Social Exergames via Shapley BanditsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584050(322-336)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581641.3584050
Girdhar NDoucet A(2023)Can we please everyone? Group recommendations in signed social networksMultimedia Tools and Applications10.1007/s11042-023-17422-283:16(48237-48260)Online publication date: 2-Nov-2023
https://doi.org/10.1007/s11042-023-17422-2
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Index Terms

Adaptive radio: achieving consensus using negative preferences
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Computer supported cooperative work
2. Social and professional topics
  1. Professional topics
    1. Computing and business
      1. Computer supported cooperative work

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Information & Contributors

Information

Published In

GROUP '05: Proceedings of the 2005 ACM International Conference on Supporting Group Work

November 2005

368 pages

ISBN:1595932232

DOI:10.1145/1099203

General Chairs:
Mark Pendergast
Florida Gulf Coast University, USA
,
Kjeld Schmidt
IT University of Copenhagen, Denmark
,
Program Chairs:
Gloria Mark
University of California, Irvine, USA
,
Mark Ackerman
University of Michigan, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2005

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GROUP05: ACM 2005 International Conference on Supporting Group Work

November 6 - 9, 2005

Florida, Sanibel Island, USA

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Overall Acceptance Rate 125 of 405 submissions, 31%

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Cited By

View all

Gabbolini GBridge D(2024)Surveying More Than Two Decades of Music Information Retrieval Research on PlaylistsACM Transactions on Intelligent Systems and Technology10.1145/368839815:6(1-68)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3688398
Gray RVillareale JFox TDallal DOntanon SArigo DJabbari SZhu J(2023)Improving Fairness in Adaptive Social Exergames via Shapley BanditsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584050(322-336)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581641.3584050
Girdhar NDoucet A(2023)Can we please everyone? Group recommendations in signed social networksMultimedia Tools and Applications10.1007/s11042-023-17422-283:16(48237-48260)Online publication date: 2-Nov-2023
https://doi.org/10.1007/s11042-023-17422-2
Ramos ROliveira LVinagre J(2023)Hybrid SkipAwareRec: A Streaming Music Recommendation SystemProgress in Artificial Intelligence10.1007/978-3-031-49008-8_22(275-287)Online publication date: 15-Dec-2023
https://doi.org/10.1007/978-3-031-49008-8_22
Felfernig AWillemsen M(2023)Handling PreferencesGroup Recommender Systems10.1007/978-3-031-44943-7_5(95-107)Online publication date: 23-Sep-2023
https://doi.org/10.1007/978-3-031-44943-7_5
Felfernig AAtas MStettinger MTran TReiterer S(2023)Group Recommender ApplicationsGroup Recommender Systems10.1007/978-3-031-44943-7_4(79-94)Online publication date: 23-Sep-2023
https://doi.org/10.1007/978-3-031-44943-7_4
Park SKaneshiro B(2022)User perspectives on critical factors for collaborative playlistsPLOS ONE10.1371/journal.pone.026075017:1(e0260750)Online publication date: 5-Jan-2022
https://doi.org/10.1371/journal.pone.0260750
Alvarado OHtun NJin YVerbert K(2022)A Systematic Review of Interaction Design Strategies for Group Recommendation SystemsProceedings of the ACM on Human-Computer Interaction10.1145/35551616:CSCW2(1-51)Online publication date: 11-Nov-2022
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Park MLee K(2022)Exploiting Negative Preference in Content-based Music Recommendation with Contrastive LearningProceedings of the 16th ACM Conference on Recommender Systems10.1145/3523227.3546768(229-236)Online publication date: 12-Sep-2022
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Park SRedmond EBerger JKaneshiro B(2022)Hitting Pause: How User Perceptions of Collaborative Playlists Evolved in the United States During the COVID-19 PandemicProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517604(1-16)Online publication date: 29-Apr-2022
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