An interactive search method based on user preferences

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.