An Interactive Search Method Based on User Preferences

Asim Roy (), Patrick Mackin (), Jyrki Wallenius (), James Corner (), Mark Keith (), Gregory Schymik () and Hina Arora ()
Additional contact information
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

Decision Analysis, 2008, vol. 5, issue 4, 203-229

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.

Keywords: interactive search; math programming; decision analysis; multiattribute; multiple criteria decision making; utility/preference; multiattribute (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ordeca:v:5:y:2008:i:4:p:203-229

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