More Web Proxy on the site http://driver.im/

Article

Designing example-critiquing interaction

Authors:

Paolo ViappianiAuthors Info & Claims

IUI '04: Proceedings of the 9th international conference on Intelligent user interfaces

Pages 22 - 29

https://doi.org/10.1145/964442.964449

Published: 13 January 2004 Publication History

Abstract

In many practical scenarios, users are faced with the problem of choosing the most preferred outcome from a large set of possibilities. As people are unable to sift through them manually, decisions support systems are often used to automatically find the optimal solution. A crucial requirement for such a system is to have an accurate model of the user's preferences.Studies have shown that people are usually unable to accurately state their preferences up front, but are greatly helped by seeing examples of actual solutions. Thus, several researchers have proposed preference elicitation strategies based on example critiquing. The essential design question in example critiquing is what examples to show users in order to best help them locate their most preferred solution.In this paper, we analyze this question based on two requirements. The first is that it must stimulate the user to express further preferences by showing the range of alternatives available. The second is that the examples that are shown must contain the solution that the user would consider optimal if the currently expressed preference model was complete so that he select it as a final solution.

References

[1]

C. Boutilier, R. Brafman, C. Geib, and D. Poole: "A Constraint-Based Approach to Preference Elicitation and Decision Making," AAAI Spring Symposium on Qualitative Decision Theory, Stanford, 1997.

[2]

R. Burke, K. Hammond, and B. Young: "The findme approach to assisted browsing," IEEE Expert 12(4), pp. 32--40, 1997.

Digital Library

[3]

G. Carenini and D. Poole: "Constructed Preferences and Value-focused Thinking: Implications for AI research on Preference Elicitation," AAAI-02 Workshop on Preferences in AI and CP: symbolic approaches - Edmonton, Canada, 2002.

[4]

J. Doyle and R. Thomason: "Background to qualitative decision theory," AI Magazine 20(2), Summer 1999.

[5]

B. Faltings, M. Torrens and P. Pu: "Solution generation with qualitative models of preferences," to appear in Computational Intelligence, special issue on qualitative decision theory, 2004, available at http:\\liawww.epfl.ch\~ faltings\compint-2004.pdf.

[6]

V. Ha and P. Haddawy: "Problem-focused incremental elicitation of multiattribute utility models," 13th Conference on Uncertainty in Artificial Intelligence, pp. 215--222, August 1997.

Digital Library

[7]

V. Ha and P. Haddawy: "Toward Case-Based Preference Elicitation: Similarity Measures on Preference Structures," 14th Conference on Uncertainty in Artificial Intelligence. 1998.

Digital Library

[8]

R.Keeney and H. Raiffa: "Decision with multiple objectives: Preferences and value tradeoffs," Cambridge University Press, 1976.

[9]

R. Keeney: "Value-Focused Thinking: A Path to Creative Decision Making," Harvard University Press, 1992.

[10]

G. Linden, S. Hanks, and N. Lesh: "Interactive assessment of user preference models: The automated travel assistant," In Proceedings of User Modeling '97, 1997.

[11]

J.W. Payne, J.R. Bettman and E.J. Johnson: "The Adaptive Decision Maker," Cambridge University Press, 1993.

[12]

P. Pu and B. Faltings: "Enriching Buyers' experiences: the SmartClient Approach," ACM SIGCHI 2000 Conference on Human Factors in Computing Systems, pp. 289--296, 2000.

Digital Library

[13]

S. Shearin and H. Lieberman: "Intelligent Profiling by Example," International Conference on Intelligent User Interfaces (IUI 2001), pp. 145--152, 2001.

Digital Library

[14]

M. Stolze: "Soft Navigation in electronic product catalogs," International Journal on Digital Libraries 3(1), pp. 60--66, 2000.

[15]

M. Torrens, R. Weigel and B. Faltings: "Java Constraint Library: bringing constraint technology on the Internet using the Java language," Workshop on Constraints and Agents (AAAI97), AAAI Technical Report WS-97-05, July 1997.

[16]

M. Torrens, B. Faltings and P. Pu: "SmartClients: Constraint Satisfaction as a Paradigm for Scaleable Intelligent Information Systems," CONSTRAINTS 7, p. 49--69, 2002.

Digital Library

[17]

M. Torrens, P. Hertzog, L. Samson and B. Faltings: "reality: a Scalable Intelligent Travel Planer, Decision Support for the Business Traveler," 18th ACM Symposium on Applied Computing, Melbourne, 2003.

Digital Library

Cited By

Medlar ALi JLiu YGlowacka DBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Critiquing-based Modeling of Subjective PreferencesProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531314(234-242)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3531314
Floridi LCowls JKing TTaddeo M(2021)How to Design AI for Social Good: Seven Essential FactorsEthics, Governance, and Policies in Artificial Intelligence10.1007/978-3-030-81907-1_9(125-151)Online publication date: 3-Nov-2021
https://doi.org/10.1007/978-3-030-81907-1_9
Li HSanner SLuo KWu G(2020)A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender SystemsProceedings of the 14th ACM Conference on Recommender Systems10.1145/3383313.3412240(13-22)Online publication date: 22-Sep-2020
https://dl.acm.org/doi/10.1145/3383313.3412240
Show More Cited By

Index Terms

Designing example-critiquing interaction
1. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Interaction design guidelines on critiquing-based recommender systems

A critiquing-based recommender system acts like an artificial salesperson. It engages users in a conversational dialog where users can provide feedback in the form of critiques to the sample items that were shown to them. The feedback, in turn, enables ...
Decision Tradeoff Using Example-Critiquing and Constraint Programming

We consider constructive preference elicitation for decision aid systems in applications such as configuration or electronic catalogs. We are particularly interested in supporting decision tradeoff, where preferences are revised in response to the ...
Preference-based search using example-critiquing with suggestions

We consider interactive tools that help users search for their most preferred item in a large collection of options. In particular, we examine example-critiquing, a technique for enabling users to incrementally construct preference models by critiquing ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

IUI '04: Proceedings of the 9th international conference on Intelligent user interfaces

January 2004

396 pages

ISBN:1581138156

DOI:10.1145/964442

Conference Chair:
Jean Vanderdonckt
University Louvain (BE)
,
Program Chairs:
Nuno Jardim Nunes
University of Madeira (PT)
,
Charles Rich
Mitsubishi Electric Research Laboratories (US)

Copyright © 2004 ACM.

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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 January 2004

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

IUI-CADUI04

Sponsor:

IUI-CADUI04: Intelligent User Interface

January 13 - 16, 2004

Funchal, Madeira, Portugal

Acceptance Rates

IUI '04 Paper Acceptance Rate 72 of 140 submissions, 51%;

Overall Acceptance Rate 746 of 2,811 submissions, 27%

Upcoming Conference

IUI '25

Sponsor:
sigai
sigai

30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

Cagliari , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

37
Total Citations
View Citations
661
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)1

Reflects downloads up to 21 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Medlar ALi JLiu YGlowacka DBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Critiquing-based Modeling of Subjective PreferencesProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531314(234-242)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3531314
Floridi LCowls JKing TTaddeo M(2021)How to Design AI for Social Good: Seven Essential FactorsEthics, Governance, and Policies in Artificial Intelligence10.1007/978-3-030-81907-1_9(125-151)Online publication date: 3-Nov-2021
https://doi.org/10.1007/978-3-030-81907-1_9
Li HSanner SLuo KWu G(2020)A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender SystemsProceedings of the 14th ACM Conference on Recommender Systems10.1145/3383313.3412240(13-22)Online publication date: 22-Sep-2020
https://dl.acm.org/doi/10.1145/3383313.3412240
Floridi LCowls JKing TTaddeo M(2020)How to Design AI for Social Good: Seven Essential FactorsScience and Engineering Ethics10.1007/s11948-020-00213-5Online publication date: 3-Apr-2020
https://doi.org/10.1007/s11948-020-00213-5
Baarslag TKaisers MLarson KWinikoff MDas SDurfee E(2017)The Value of Information in Automated NegotiationProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems10.5555/3091125.3091185(391-400)Online publication date: 8-May-2017
https://dl.acm.org/doi/10.5555/3091125.3091185
Andjelkovic IParra DO'Donovan JVassileva JBlustein JAroyo LD'Mello S(2016)MoodplayProceedings of the 2016 Conference on User Modeling Adaptation and Personalization10.1145/2930238.2930280(275-279)Online publication date: 13-Jul-2016
https://dl.acm.org/doi/10.1145/2930238.2930280
Parra DBrusilovsky PTrattner CKuflik TStock OChai JKrüger A(2014)See what you want to seeProceedings of the 19th international conference on Intelligent User Interfaces10.1145/2557500.2557542(235-240)Online publication date: 24-Feb-2014
https://dl.acm.org/doi/10.1145/2557500.2557542
Wang Z(2014)Personalising live zooming using the ePlayerMultimedia Systems10.1007/s00530-013-0347-820:6(721-733)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1007/s00530-013-0347-8
Vig JSen SRiedl J(2012)The Tag GenomeACM Transactions on Interactive Intelligent Systems10.1145/2362394.23623952:3(1-44)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1145/2362394.2362395
Pommeranz ABroekens JWiggers PBrinkman WJonker C(2012)Designing interfaces for explicit preference elicitationUser Modeling and User-Adapted Interaction10.1007/s11257-011-9116-622:4-5(357-397)Online publication date: 1-Oct-2012
https://dl.acm.org/doi/10.1007/s11257-011-9116-6
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents