Adaptive Radio: Achieving Consensus Using Negative Preferences
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Association for Computing Machinery
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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.
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shared spaces, audio, collaborative systems, ubiquitous computing
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Number of citations to item: 59
- Mouzhi Ge, Fabio Persia (2017): Research Challenges in Multimedia Recommender Systems, In: 2017 IEEE 11th International Conference on Semantic Computing (ICSC), doi:10.1109/icsc.2017.31
- Minju Park, Kyogu Lee (2022): Exploiting Negative Preference in Content-based Music Recommendation with Contrastive Learning, In: Proceedings of the 16th ACM Conference on Recommender Systems, doi:10.1145/3523227.3546768
- Nitin Mishra (2019): Improving performance of collaborative recommender system using combination of learning techniques, In: International Robotics & Automation Journal 2(5), doi:10.15406/iratj.2019.05.00174
- Harita Mehta, Punam Bedi, Veer Sain Dixit (2012): OCRG: A proposed recommender for mitigating new user problem, In: 2012 World Congress on Information and Communication Technologies, doi:10.1109/wict.2012.6409132
- Thorsten Hennig-Thurau, André Marchand, Paul Marx (2012): Can Automated Group Recommender Systems Help Consumers Make Better Choices?, In: Journal of Marketing 5(76), doi:10.1509/jm.10.0537
- Alexander Schindler, Andreas Rauber (2011): Clubmixer: A Presentation Platform for MIR Projects, In: Lecture Notes in Computer Science, doi:10.1007/978-3-642-27169-4_10
- Iván Cantador, Pablo Castells (2012): Group Recommender Systems: New Perspectives in the Social Web, In: Intelligent Systems Reference Library, doi:10.1007/978-3-642-25694-3_7
- Pragya Dwivedi, Kamal K. Bharadwaj (2013): e‐Learning recommender system for a group of learners based on the unified learner profile approach, In: Expert Systems 2(32), doi:10.1111/exsy.12061
- V Ramanjaneyulu Yannam, Jitendra Kumar, Korra Sathya Babu, Bidyut Kumar Patra (2022): Enhancing the accuracy of group recommendation using slope one, In: The Journal of Supercomputing 1(79), doi:10.1007/s11227-022-04664-4
- So Yeon Park, Emily Redmond, Jonathan Berger, Blair Kaneshiro (2022): Hitting Pause: How User Perceptions of Collaborative Playlists Evolved in the United States During the COVID-19 Pandemic, In: CHI Conference on Human Factors in Computing Systems, doi:10.1145/3491102.3517604
- Federica Cena, Luca Console, Fabiana Vernero (2022): How to deal with negative preferences in recommender systems: a theoretical framework, In: Journal of Intelligent Information Systems 1(60), doi:10.1007/s10844-022-00705-9
- Nancy Girdhar, Antoine Doucet (2023): Can we please everyone? Group recommendations in signed social networks, In: Multimedia Tools and Applications 16(83), doi:10.1007/s11042-023-17422-2
- Shahab H. Kaka Ali, Ibrahim Berkan Aydilek (2021): Shopping and Basket Analysis by Using an Improved Apriori Algorithm in WEKA, In: Journal of Studies in Science and Engineering 2(1), doi:10.53898/josse2021126
- Adrián Valera, Alvaro Lozano Murciego, María N. Moreno-García (2021): Group Recommender Systems in the Music Domain: A Systematic Literature Review, In: Advances in Intelligent Systems and Computing, doi:10.1007/978-3-030-87687-6_28
- Arto Lehtiniemi, Jarno Ojala (2012): MyTerritory, In: Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia, doi:10.1145/2406367.2406410
- Müslüm Atas, Alexander Felfernig, Seda Polat-Erdeniz, Andrei Popescu, Thi Ngoc Trang Tran, Mathias Uta (2021): Towards psychology-aware preference construction in recommender systems: Overview and research issues, In: Journal of Intelligent Information Systems 3(57), doi:10.1007/s10844-021-00674-5
- Sriharsha Dara, C. Ravindranath Chowdary, Chintoo Kumar (2019): A survey on group recommender systems, In: Journal of Intelligent Information Systems 2(54), doi:10.1007/s10844-018-0542-3
- Günther Schatter, Benjamin Zeller (2007): Design and Implementation of an Adaptive Digital Radio DAB using Content Personalization on the Basis of Standards, In: IEEE Transactions on Consumer Electronics 4(53), doi:10.1109/tce.2007.4429224
- Wei Li, XiaoDong Fu, QingSong Huang, Li Liu (2016): Evaluating on online services based on social choice theory, In: 2016 Chinese Control and Decision Conference (CCDC), doi:10.1109/ccdc.2016.7532170
- Oscar Alvarado, Nyi Nyi Htun, Yucheng Jin, Katrien Verbert (2022): A Systematic Review of Interaction Design Strategies for Group Recommendation Systems, In: Proceedings of the ACM on Human-Computer Interaction CSCW2(6), doi:10.1145/3555161
- Claudio Baccigalupo, Enric Plaza (2000): A Case-Based Song Scheduler for Group Customised Radio, In: Lecture Notes in Computer Science, doi:10.1007/978-3-540-74141-1_30
- Hannu Kukka, Rodolfo Patino, Timo Ojala (2009): UbiRockMachine, In: Proceedings of the 8th International Conference on Mobile and Ubiquitous Multimedia, doi:10.1145/1658550.1658559
- Anthony Jameson, Barry Smyth (2000): Recommendation to Groups, In: Lecture Notes in Computer Science, doi:10.1007/978-3-540-72079-9_20
- Robert C. Gray, Jennifer Villareale, Thomas Boyd Fox, Diane H. Dallal, Santiago Ontanon, Danielle Arigo, Shahin Jabbari, Jichen Zhu (2023): Improving Fairness in Adaptive Social Exergames via Shapley Bandits, In: Proceedings of the 28th International Conference on Intelligent User Interfaces, doi:10.1145/3581641.3584050
- J. Bobadilla, F. Ortega, A. Hernando, A. Gutiérrez (2013): Recommender systems survey, In: Knowledge-Based Systems, doi:10.1016/j.knosys.2013.03.012
- Stefan Dimitri Ziaras, Wolfgang Wörndl (2019): Strategy-Specific Preference Elicitation for Group Recommender, In: Proceedings of Mensch und Computer 2019, doi:10.1145/3340764.3344452
- F. Ortega, J. Bobadilla, A. Hernando, A. Gutiérrez (2013): Incorporating group recommendations to recommender systems: Alternatives and performance, In: Information Processing & Management 4(49), doi:10.1016/j.ipm.2013.02.003
- Markus Tschersich (2011): Design guidelines for mobile group recommender systems to handle inaccurate or missing location data, In: Proceedings of the fifth ACM conference on Recommender systems, doi:10.1145/2043932.2044006
- KuanTing Liu, Roger Andersson Reimer (2008): Social playlist, In: Proceedings of the 10th international conference on Human computer interaction with mobile devices and services, doi:10.1145/1409240.1409299
- So Yeon Park, Blair Kaneshiro (2021): Social Music Curation That Works, In: Proceedings of the ACM on Human-Computer Interaction CSCW1(5), doi:10.1145/3449191
- Yongli Ren, Gang Li, Wanlei Zhou (2014): A survey of recommendation techniques based on offline data processing, In: Concurrency and Computation: Practice and Experience 15(27), doi:10.1002/cpe.3370
- Kevin McCarthy, Lorraine McGinty, Barry Smyth (2000): Case-Based Group Recommendation: Compromising for Success, In: Lecture Notes in Computer Science, doi:10.1007/978-3-540-74141-1_21
- Latifa Baba Hamed, Sofiane Abbar, Amine Haouari (2012): The impact of negative preferences on a recommendation process, In: 2012 International Conference on Multimedia Computing and Systems, doi:10.1109/icmcs.2012.6320217
- David Sprague, Fuqu Wu, Melanie Tory (2008): Music selection using the PartyVote democratic jukebox, In: Proceedings of the working conference on Advanced visual interfaces, doi:10.1145/1385569.1385652
- Ilaria Lombardi, Fabiana Vernero (2017): What and who with: A social approach to double-sided recommendation, In: International Journal of Human-Computer Studies, doi:10.1016/j.ijhcs.2017.01.001
- Chintoo Kumar, C. Ravindranath Chowdary (2022): A study on the role of uninterested items in group recommendations, In: Electronic Commerce Research 4(23), doi:10.1007/s10660-021-09526-4
- Toon De Pessemier, Simon Dooms, Luc Martens (2013): Comparison of group recommendation algorithms, In: Multimedia Tools and Applications 3(72), doi:10.1007/s11042-013-1563-0
- Kevin Eustice, V. Ramakrishna, Nam Nguyen, Peter Reiher (2008): The Smart Party: A Personalized Location-Aware Multimedia Experience, In: 2008 5th IEEE Consumer Communications and Networking Conference, doi:10.1109/ccnc08.2007.204
- Badr Ait Hammou, Ayoub Ait Lahcen, Salma Mouline (2019): A distributed group recommendation system based on extreme gradient boosting and big data technologies, In: Applied Intelligence 12(49), doi:10.1007/s10489-019-01482-9
- Evgeny Frolov, Ivan Oseledets (2016): Fifty Shades of Ratings, In: Proceedings of the 10th ACM Conference on Recommender Systems, doi:10.1145/2959100.2959170
- Berardina De Carolis (2011): Adapting News and Advertisements to Groups, In: Human-Computer Interaction Series, doi:10.1007/978-0-85729-352-7_11
- Wei Zeng, Ming-Sheng Shang (2010): Effects of negative ratings on personalized recommendation, In: 2010 5th International Conference on Computer Science & Education, doi:10.1109/iccse.2010.5593607
- Claudio Baccigalupo, Enric Plaza (2007): Poolcasting: A Social Web Radio Architecture for Group Customisation, In: Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS'07), doi:10.1109/axmedis.2007.19
- Takuma Yabe, Keiichi Zempo (2020): Negative confidence recommendation system avoids local solution based on user’s negative reactions, In: 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE), doi:10.1109/gcce50665.2020.9292036
- Danielle H. Lee, Peter Brusilovsky (2009): Reinforcing Recommendation Using Implicit Negative Feedback, In: Lecture Notes in Computer Science, doi:10.1007/978-3-642-02247-0_47
- Yu Liu, Bai Wang, Bin Wu, Xuelin Zeng, Jing Shi, Yunlei Zhang (2016): CoGrec: A Community-Oriented Group Recommendation Framework, In: Communications in Computer and Information Science, doi:10.1007/978-981-10-2053-7_24
- Jichen Zhu, Santiago Ontanon (2019): Experience Management in Multi-player Games, In: 2019 IEEE Conference on Games (CoG), doi:10.1109/cig.2019.8848030
- Sarik Ghazarian, Mohammad Ali Nematbakhsh (2015): Enhancing memory-based collaborative filtering for group recommender systems, In: Expert Systems with Applications 7(42), doi:10.1016/j.eswa.2014.11.042
- Ladislav Peska, Peter Vojtas (2013): Negative implicit feedback in e-commerce recommender systems, In: Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics, doi:10.1145/2479787.2479800
- So Yeon Park, Blair Kaneshiro (2022): User perspectives on critical factors for collaborative playlists, In: PLOS ONE 1(17), doi:10.1371/journal.pone.0260750
- Arto Lehtiniemi, Jarno Ojala, Kaisa Väänänen (2016): Socially Augmented Music Discovery with Collaborative Playlists and Mood Pictures, In: Interacting with Computers, doi:10.1093/iwc/iww032
- Lu Jiang, Yuqi Wang, Shasha Xie, Jun Wu, Minghao Yin, Jianan Wang (2022): Which courses to choose? recommending courses to groups of students in online tutoring platforms, In: Applied Intelligence 10(53), doi:10.1007/s10489-022-03993-4
- Giovanni Gabbolini, Derek Bridge (2024): Surveying More Than Two Decades of Music Information Retrieval Research on Playlists, In: ACM Transactions on Intelligent Systems and Technology 6(15), doi:10.1145/3688398
- Alexander Felfernig, Ludovico Boratto, Martin Stettinger, Marko Tkalčič (2018): Group Recommender Applications, In: SpringerBriefs in Electrical and Computer Engineering, doi:10.1007/978-3-319-75067-5_4
- Luiz Augusto Pizzato, Tomek Rej, Kalina Yacef, Irena Koprinska, Judy Kay (2011): Finding Someone You Will Like and Who Won’t Reject You, In: Lecture Notes in Computer Science, doi:10.1007/978-3-642-22362-4_23
- Adrián Valera, Álvaro Lozano Murciego, María N. Moreno-García (2021): Context-Aware Music Recommender Systems for Groups: A Comparative Study, In: Information 12(12), doi:10.3390/info12120506
- Wei Li, Jian Xu, Qing Bao, Rujia Shen, Hao Yuan, Ming Xu (2020): An Adaptive Aggregation Method Based on Movie Genre for Group Recommendation, In: 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI), doi:10.1109/ictai50040.2020.00022
- Harita Mehta, Veer Sain Dixit, Punam Bedi (2012): Refinement of recommendations based on user preferences, In: 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA), doi:10.1109/isda.2012.6416591
- Nikos Bikakis, Karim Benouaret, Dimitris Sacharidis (2015): Finding desirable objects under group categorical preferences, In: Knowledge and Information Systems 1(49), doi:10.1007/s10115-015-0886-8