Combining Visual Layout and Lexical Cohesion Features for Text Segmentation
Min‐Yen Kan · 2001
We propose integrating features from lexical cohesion with elements from layout recognition to build a composite framework. We use supervised machine learning on this composite feature set to derive discourse structure on the topic level. We demonstrate a system based on this principle and use both an intrinsic evaluation as well as the task of genre classification to assess its performance.