The Semantic Accessibility Scale (SAS) is one of the criteria for systematically assessing the semantic readability of corpus texts. With the advent of the Internet, English language content has been widely distributed. This constitutes an adequate corpus for corpus research. However, how to assign and evaluate the semantic acceptability of English literary texts with the aid of corpus has become a hot topic of study for academics around the world. In this paper, we propose an analysis method for corpus semantic acceptance based on the Kano model. This method combines the Kano model with corpus semantic acceptance. Initially, the method identifies the initial corpus semantic acceptance demand items using the initial corpus semantic acceptance identification questionnaire. The Kano categories of each requirement item are then identified and filtered based on the second Kano questionnaire. In this paper, we propose a Kano-based method for corpus semantic acceptance requirement analysis and apply Kano theory to corpus semantic acceptance requirement analysis. First, the corpus semantic acceptance requirements are classified into corresponding Kano categories and filtered using a Kano survey; second, the initial weights of the corpus semantic acceptance requirements are determined using the coarse number method; and finally, the initial weights of the requirements are adjusted using the corresponding Kano adjustment coefficients to obtain the final weights of the corpus semantic acceptance requirements.
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