Experiments on sentence boundary detection in user-generated web content

Abstract

Sentence Boundary Detection (SBD) is a very important prerequisite for proper sentence analysis in different Natural Language Processing tasks. During the last years, many SBD methods have been used in the transcriptions produced by Automatic Speech Recognition systems and in well-structured texts (e.g. news, scientific texts). However, there are few researches about SBD in informal user-generated content such as web reviews, comments, and posts, which are not necessarily well written and structured. In this paper, we adapt and extend a well-known SBD method to the domain of the opinionated texts in the web. Particularly, we evaluate our proposal in a set of online product reviews and compare it with other traditional SBD methods. The experimental results show that we outperform these other methods.