Topic segmentation for short texts

Abstract

Topic segmentation, which aims to find the boundaries between topic blocks in a text, is an important task for semantic analysis of texts. Although different solutions have been proposed for the task, many limitations and difficulties exist in the approaches. In particular most of the methods do not work well for such case as short texts, internet news and student's writings. In this paper, we focus on the short texts and present a method for topic segmentation. It can overcome the limitations in previous works. In preliminary experiments, the method show the accuracy of topic segmentation is increased effectively.