This article proposes the modified KNN (K Nearest Neighbor) algorithm which receives a string vector as its input data and isapplied to the text segmentation. The results from applying the string vector based algorithms to the text categorizations were successful in previous works, and the text segmentation is able to be viewed into a binary classification where each adjacent paragraph pair is classified into boundary or continuance. In the proposedsystem, a list of adjacent paragraph pairs is generated by sliding a text with the two sized window, each pair is classified by theproposed KNN version, and the boundary is put between the pairs which are classified into boundary. The proposed KNN version isempirically validated as the better approach in deciding whether each pair should be separated from each other or not in news articles and opinions. We need to define and characterizemathematically more operations on string vectors for modifying more advanced machine learning algorithms.