Adaptive radio: achieving consensus using negative preferences

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.

[1]  M. Diehl,et al.  Why Groups are less Effective than their Members: On Productivity Losses in Idea-generating Groups , 1994 .

[2]  J. Lanza,et al.  Elevator Music: A Surreal History of Muzak, Easy-Listening, and Other Moodsong; Revised and Expanded Edition , 1994 .

[3]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[4]  Joseph F. McCarthy,et al.  UniCast, OutCast & GroupCast: An Exploration of New Interaction Paradigms for Ubiquitous, Peripheral Displays , 2001 .

[5]  Joseph F. McCarthy,et al.  MUSICFX: an arbiter of group preferences for computer supported collaborative workouts , 2000, CSCW '00.

[6]  Sara Reese Hedberg.  After Desktop Computing: A Progress Report on Smart Environments Research , 2000, IEEE Intell. Syst..

[7]  John Riedl,et al.  PolyLens: A recommender system for groups of user , 2001, ECSCW.

[8]  Kristian J. Hammond,et al.  Flytrap: intelligent group music recommendation , 2002, IUI '02.

[9]  Stephanie Forrest,et al.  Generating biomorphs with an aesthetic immune system , 2002 .

[10]  K. Fiedler,et al.  Organizational Behavior and Human Decision Processes , 2002 .

[11]  Stephen Huxley,et al.  Lowest common denominator , 1999 .

[12]  A. Van Hiel,et al.  Information Acquisition Bias during the Preparation of Group Discussion , 2003 .

[13]  James C. French,et al.  Flycasting: On the Fly Broadcasting , 2001, DELOS.

[14]  Stephanie Forrest,et al.  Information Immune Systems , 2003, Genetic Programming and Evolvable Machines.

[15]  Gregory D. Abowd,et al.  The Aware Home: A Living Laboratory for Ubiquitous Computing Research , 1999, CoBuild.

[16]  Serge Moscovici,et al.  Toward A Theory of Conversion Behavior , 1980 .

[17]  Thomas W. Malone,et al.  Intelligent Information Sharing Systems , 1986 .

[18]  Douglas Muzzio,et al.  APPROVAL VOTING , 1983 .

[19]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[20]  Steven McCanne,et al.  An evaluation of preference clustering in large-scale multicast applications , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[21]  Joseph F. McCarthy,et al.  UniCast, OutCast & GroupCast: Three Steps Toward Ubiquitous, Peripheral Displays , 2001, UbiComp.