Design and Implementation of Preference-Based Search

Abstract

Preference-based search is the problem of finding an item that matches best with a user's preferences. User studies show that example-based tools for preference-based search can achieve significantly higher accuracy when they are complemented with suggestions chosen to inform users about the available choices. We present FlatFinder, an implementation of an example-based tool and discuss how such a tool as well as suggestions can be efficiently implemented even for large product databases.

Preference-Search based Recommendation System for Accommodation Facilitator : A Review

“…Preference-based search can be defined as "Given a collection O = {o1, …, on} of n options, preferencebased search (PBS) is an interactive process that helps identify the most preferred option, called the target option ot , based on a set of preferences that they have stated on the attributes of the target [1].…”

“…Considering the types of critiquing-based approaches for recommending products to consumers online, this study will acquire the preference-based search tool and will club it with the example-critiquing method. Preference-based search is a tool for the elicitation of users' initial preferences, whereas example-critiquing is a method that allow users to rectify their preferences to locate the ideal item that suits well their requirements [1].…”

“…This method invites users to state their preferences (preference-based search) explicitly. This is formally defined the problem as [1]:…”

“…It was found that searching real estate assets online does not benefit renters' in terms of time, flexibility and intuitive results [3]. Search engines generally do a good job by helping users find what they are looking for, however many people find it hard to match their preferences to a query that is likely to produce the desired search results [1]. Using recommendation systems technology can address the problem of mapping user's preferences to items that are likely to meet them [1].…”

“…Search engines generally do a good job by helping users find what they are looking for, however many people find it hard to match their preferences to a query that is likely to produce the desired search results [1]. Using recommendation systems technology can address the problem of mapping user's preferences to items that are likely to meet them [1]. Recommendation systems contains such software gives suggestions for items useful to user [2].…”