Abstract
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.
This study was supported in part by JSPS Grant-in-Aid for Scientific Research [KAKENHI(B) No. 22300074].
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Huynh, VN., Yan, H., Ryoke, M., Nakamori, Y. (2011). Fuzzy Target-Based Multi-feature Evaluation of Traditional Craft Products. In: Xiong, H., Lee, W.B. (eds) Knowledge Science, Engineering and Management. KSEM 2011. Lecture Notes in Computer Science(), vol 7091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25975-3_29
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DOI: https://doi.org/10.1007/978-3-642-25975-3_29
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