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Strategy-Specific Preference Elicitation for Group Recommender

Published: 08 September 2019 Publication History

Abstract

Group recommender systems propose items to a group of users by taking the preferences of individuals into account. Preference elicitation interfaces in existing solutions mostly use 5-point rating scales and are not tailored for group tasks and the underlying aggregation strategies. There is little work that addresses the design of suitable preference elicitation interfaces for group scenarios. In this paper, we propose, prototype, and evaluate novel user interface concepts that are tailored for aggregation strategies. In total, we introduce 8 solutions which seek to make the underlying strategies more transparent to the users. We present two user interfaces for each selected strategy and compare them in a user study. The results demonstrate that the presented prototypes were well received by most of the participants. Except for one draft solution, most participants agreed or strongly agreed that the proposed user interfaces are suitable for the respective strategy. Moreover, our findings suggest that there is a correlation between the complexity of aggregation strategies and the feedback received by the participants. This implies that it makes sense to hide the underlying logic when using complicated strategies. Furthermore, the results indicate that user interface elements should be tailored to the aggregation strategy.

References

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Alexander Felfernig, Ludovico Boratto, Martin Stettinger, and Marko Tkalčič. 2018. Decision Tasks and Basic Algorithms. In Group Recommender Systems: An Introduction. Springer International Publishing.
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Judith Masthoff. 2011. Group Recommender Systems: Combining Individual Models. In Recommender Systems Handbook, Francesco Ricci, Lior Rokach, Bracha Shapira, Paul B. Kantor (Eds.). Springer US, Boston MA, 677--702.
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Judith Masthoff. 2004. Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers. User Modeling and User-Adapted Interaction 14, 1, pp. 37--85.
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Dennis L. Chao, Justin Balthrop, and Stephanie Forrest. 2005. Adaptive radio: achieving consensus using negative preferences. In Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work (GROUP '05). ACM, New York, NY, USA, 120--123.
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Kevin McCarthy, Maria Salamó, Lorcan Coyle, Lorraine McGinty, Barry Smyth, and Paddy Nixon. 2006. Group recommender systems: a critiquing based approach. In Proceedings of the 11th international conference on Intelligent user interfaces (IUI '06). ACM, New York, NY, USA, 267--269.
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Anthony Jameson. 2004. More than the sum of its members: challenges for group recommender systems. In Proceedings of the working conference on Advanced visual interfaces (AVI '04). ACM, New York, NY, USA, 48--54.
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Martin Stettinger, Alexander Felfernig, Gerhard Leitner, Stefan Reiterer, and Michael Jeran. 2015. Counteracting Serial Position Effects in the CHOICLA Group Decision Support Environment. In Proceedings of the 20th International Conference on Intelligent User Interfaces (IUI '15). ACM, New York, NY, USA, 148--157.
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Ingrid A Christensen, and Silvia Schiaffino Christensen. 2011. Entertainment recommender systems for group of users. Expert Systems with Applications, 38, 11, 14127--14135.
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Gerald Ninaus, Alexander Felfernig, Martin Stettinger, Stefan Reiterer, Gerhard Leitner, Leopold Weninger, and Walter Schanil. 2014. INTELLIREQ: intelligent techniques for software requirements engineering. In Proceedings of the Twenty-first European Conference on Artificial Intelligence (ECAI'14), Torsten Schaub, Gerhard Friedrich, and Barry O'Sullivan (Eds.). IOS Press, Amsterdam, The Netherlands, The Netherlands, 1161--1166.
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Iván Cantador, and Pablo Castells. 2012. Group Recommender Systems: New Perspectives in the Social Web. In Recommender Systems for the Social Web. Springer, Berlin Heidelberg, 139--157.

Cited By

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  • (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
  • (2022)Towards a Construction Kit for Visual Recommender SystemsProceedings of the 2022 International Conference on Advanced Visual Interfaces10.1145/3531073.3534484(1-3)Online publication date: 6-Jun-2022

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cover image ACM Other conferences
MuC '19: Proceedings of Mensch und Computer 2019
September 2019
863 pages
ISBN:9781450371988
DOI:10.1145/3340764
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 the author(s) 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: 08 September 2019

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Author Tags

  1. group recommender systems
  2. social choice
  3. user interfaces
  4. user study

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  • Short-paper
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  • Refereed limited

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MuC'19
MuC'19: Mensch-und-Computer
September 8 - 11, 2019
Hamburg, Germany

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Cited By

View all
  • (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
  • (2022)Towards a Construction Kit for Visual Recommender SystemsProceedings of the 2022 International Conference on Advanced Visual Interfaces10.1145/3531073.3534484(1-3)Online publication date: 6-Jun-2022

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