Text Segmentation by Clustering Cohesion

Abstract

An automatic linear text segmentation in order to detect the best topic boundaries is a difficult and very useful task in many text processing systems. Some methods have tried to solve this problem with reasonable results, but they present some drawbacks as well. In this work, we propose a new method, called ClustSeg, based on a predefined window and a clustering algorithm to decide the topic cohesion. We compare our proposal against the best known methods, with a better performance against these algorithms.

Semantic Based Text Block Segmentation Using WordNet

“…Usually, they obtain linear segmentations, where the output is a document divided into sequences of adjacent segments [6], [7]. Another approach is a hierarchical segmentation; the outputs of these methods try to identify the document structure, usually chapters and multiple levels of sub-chapters [8].…”