In this research, we propose the string vector based KNN variants, and apply them to the keyword extraction. The initial KNN version was previously modified into the string vector-based version, and the keyword extraction was mapped into a binary classification, to apply it. In this research, we mention the three KNN variants, in the case of the numerical vector-based versions: one where the selected nearest neighbors are discriminated by their similarities, one where the attributes are discriminated by their correlations with the categories, and one where the training examples are discriminate by their credits. In this research, the three KNN variants are modified into the string vector-based versions, as the approaches to the keyword extraction, as well as the initial KNN version. The goal of this research is to improve the keyword extraction performance by modifying them so.