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Nowadays,the aesthetic aspect of products has become a critical factor in achieving higher consumer satisfaction.As a methodology，Kansei Engineering(KE)has been developed to deal with consumers subjective impressions and images of a product into the design elements of the product.One central step amongst KE is to generate the Kansei profiles of the products on different Kansei attributes.The subjecfive assessments provided by the subjects in KE are usually conceptually vague with uncertainty frequently represented in linguistic forms.Toward this end，this paper tries to cope thoroughly with the uncertainty of Kansei in KE.To do so,a probabilistic approach is first proposed to generate Kansei profiles of the products involving the "individual" uncertainty，“group" uncertainty, and the partial semantic overlapping of Kansei.Our generated Kansei profile results with a probability distribution on a set of linguistic Kansei labels.The main advantages of our approach to generating Kansei profiles are its ability to model individual uncertainty,group uncertainty,as well as semantic overlapping of Kansei.