Abstract

In this research, we propose that the graph based KNN should be applied to the text segmentation task, as well as other tasks of text mining. The text segmentation may be interpreted into the binary task of texts where each pair of adjacent sentences or paragraphs is classified into whether we put the boundary between topics, or not, and the ontology which has been used as the popular and standard knowledge representation is given as a graph. In this research, we encode the adjacent sentence or paragraph pairs into graphs, and use the graph based K Nearest Neighbor for the text segmentation task. As benefits from this research, we may expect the more graphical, symbolic, and compact representations of texts as well as the improved performance. Therefore, the goal of this research is to implement the text segmentation system with the benefits.

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