Survey coding is a process of transforming respondents' responses or description into a code in the process of data analysis. This is an expensive task and this is the reason for social scientists or other professionals in charge of designing and administering surveys tend to avoid the inclusion of many open-ended questions in their surveys. They tend to rely more on the less expensive multiple-choice questions, which by definition do not require a coding phase. However multiple-choice questions strictly limit the respondents’ possible answers. This study aims at automating the survey coding process using transformed features. Five intelligent coders were developed using k Nearest Neighbor
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