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An Interactive Search Method Based on User Preferences

Author

Listed:
  • Asim Roy

    (Department of Information Systems, Arizona State University, Tempe, Arizona 85287)

  • Patrick Mackin

    (College of Business and Technology, Black Hills State University, Spearfish, South Dakota 57779)

  • Jyrki Wallenius

    (Department of Business Technology, Helsinki School of Economics, 00100 Helsinki, Finland)

  • James Corner

    (Department of Management Systems, Waikato Management School, University of Waikato, Private Bag 3105, Hamilton, New Zealand)

  • Mark Keith

    (Department of Information Systems, Arizona State University, Tempe, Arizona 85287)

  • Gregory Schymik

    (Department of Information Systems, Arizona State University, Tempe, Arizona 85287)

  • Hina Arora

    (Department of Information Systems, Arizona State University, Tempe, Arizona 85287)

Abstract

This paper presents a general method for interactively searching for objects (alternatives) in a large collection the contents of which are unknown to the user and where the objects are defined by a large number of discrete-valued attributes. Briefly, the method presents an object and asks the user to indicate his or her preference for the object. The method allows preference indications in two basic modes: (1) by assignment of objects to predefined preference categories such as high, medium, and low preference or (2) by direct preference comparison of objects such as “object A preferred to object B.” From these preference statements, the method learns about the user's preferences and constructs an approximation to a value or preference function of the user (additive or multiplicative) at each iteration. It then uses this approximate preference function to rerank the objects in the collection and retrieve the top-ranked ones to present to the user at the next iteration. The process terminates when the user is satisfied with the list of top-ranked objects. This method can also be used to solve general multiattribute discrete alternative problems, where the alternatives are known with certainty and described by a set of discrete-valued attributes. Test results are reported and application possibilities are discussed.

Suggested Citation

  • Asim Roy & Patrick Mackin & Jyrki Wallenius & James Corner & Mark Keith & Gregory Schymik & Hina Arora, 2008. "An Interactive Search Method Based on User Preferences," Decision Analysis, INFORMS, vol. 5(4), pages 203-229, December.
    • Handle: RePEc:inm:ordeca:v:5:y:2008:i:4:p:203-229
    DOI: 10.1287/deca.1080.0125
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Tino Werner, 2022. "Elicitability of Instance and Object Ranking," Decision Analysis, INFORMS, vol. 19(2), pages 123-140, June.
    2. Zhang Li Li, 2011. "Group Identification Method for Features of Human Capital Inner Quality Structure," Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 2(3), pages 102-105, September.
    3. Peters, M. & Ketter, W., 2013. "Towards autonomous decision-making: A probabilistic model for learning multi-user preferences," ERIM Report Series Research in Management ERS-2013-007-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. L. Robin Keller & Ali Abbas & Manel Baucells & Vicki M. Bier & David Budescu & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Ahti Salo & George Wu, 2010. "From the Editors..," Decision Analysis, INFORMS, vol. 7(4), pages 327-330, December.
      • L. Robin Keller & Manel Baucells & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Gregory S. Parnell & Ahti Salo, 2008. "From the Editors..," Decision Analysis, INFORMS, vol. 5(4), pages 173-176, December.
      • L. Robin Keller & Manel Baucells & Kevin F. McCardle & Gregory S. Parnell & Ahti Salo, 2007. "From the Editors..," Decision Analysis, INFORMS, vol. 4(4), pages 173-175, December.
      • L. Robin Keller & Manel Baucells & John C. Butler & Philippe Delquié & Jason R. W. Merrick & Gregory S. Parnell & Ahti Salo, 2009. "From the Editors ..," Decision Analysis, INFORMS, vol. 6(4), pages 199-201, December.
    5. Nikolaos Argyris & Alec Morton & José Rui Figueira, 2014. "CUT: A Multicriteria Approach for Concavifiable Preferences," Operations Research, INFORMS, vol. 62(3), pages 633-642, June.

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