Fuzzy target-based multi-feature evaluation of traditional craft products

This paper introduces our research work in fuzzy target-oriented decision analysis and its application to kansei-based evaluation of traditional crafts. After a brief introduction into fuzzy target-oriented decision analysis, we formulate a general target-oriented approach to multi-attribute evaluation problem for personalized recommendation. The central idea of this approach is to first interpret a particular user's request as a target (or benchmark) at which the user would be only interested in candidates meeting this target, and then use a combination of target-oriented decision analysis and aggregation operators for defining an evaluation function that quantifies how well a candidate meets the user's target. As for illustration, we will introduce a target-based evaluation method for multi-feature ranking of traditional craft products using kansei data and preferences specified by consumers, where product items are assessed according to the so-called kansei features, and kansei data are treated as categorical data.