An Interactive Search Method Based on User Preferences

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.

Value Orientation Evaluation and Psychological Regulation Based on Personality Traits

“…Cooper et al added a non-zero limit on the value parameter to the method, which is more conducive to obtaining the individual feature information of the evaluated object (Cooperabb, Ruiz, & Sirvent, 2009), (Cooper & Tone, 1997), (Charnes, Cooper, & Rhodes, 1978). Asim Roy et al proposed an interactive optimization model that can achieve the individual preference characteristics of each evaluation object and use the information to determine the optimal decision (Roy, Mackin, Wallenius et al, 2008). Psychological assessment is a method of measuring an individual's psychological features according to the pre-made scale, then assessing, identifying the type of the individual, and identifying the individual traits of the subject.…”

CUT: A Multicriteria Approach for Concavifiable Preferences

“…In addition to the additive case (e.g. Stewart, 1987;Jacquet-Lagrèze, Meziani and Slowinski, 1987;Roy et al, 2008), the IMOP literature has also considered other value function specifications. Geoffrion, Dyer, Feinberg (1972) and Zionts and Wallenius (1983) consider the case of a concave value function.…”

Concept-based document classification using Wikipedia and value function

“…During the last decade, considerable progress has been made in the development of intelligent information retrieval (IR) systems to cope with the information obesity of modern society (Calegari & Sanchez, 2008;Li et al, 2010;López-Herrera, Herrera-Viedma, & Herrera, 2009a,b;Malo, Siitari, & Sinha, 2010;Roy et al, 2009). The reasons for the improved performance appear to be at least twofold.…”

“…Extensive research has been performed to improve the use of preference information; see for example Nyongesa and Maleki-dizaji (2006), Rajapakse and Denham (2006), and Roy et al (2009), and their references. In particular, many of the recently proposed approaches are based on intelligent algorithms like genetic programming, which enable the systems to automatically learn the search queries from a small collection of example documents and preference statements supplied by the user (López-Herrera et al, 2009a,b;.…”