Personalised Fuzzy Recommendation for High Involvement Products

Abstract

In this paper we introduce a content-based recommendation approach for assisting buyers of high involvement products with their purchasing choice. The approach incorporates a group-based, fuzzy multi-criteria method and provides personalized recommendation to end-users of e-Furniture. E-Furniture is an agent-based system that offers decision making and process networking solutions to furniture manufacturing SMEs. Two are the main characteristics of the proposed approach: (i) it handles vagueness in customer preferences and seller evaluations on furniture products by utilizing the 2-tuple fuzzy linguistic information processing model and ii) it follows a similarity degree-based aggregation technique to derive an objective assessment for furniture bundles and individual furniture products that can match the customer preferences. A numerical example is given as a proof of concept, to demonstrate the applicability of the approach for providing recommendations to customers.