An approach to abstractive text summarization

Huong Thanh Le, Tien Manh Le

Abstract: ive summarization is the technique of generating a summary of a text from its main ideas, not by copying verbatim most salient sentences from text. This is an important and challenge task in natural language processing. In this paper, we propose an approach to abstractive text summarization based on discourse rules, syntactic constraints, and word graph. Discourse rules and syntactic constraints are used in the process of generating sentences from keywords. Word graph is used in the sentence combination process to represent word relations in the text and to combine several sentences into one. Experimental results show that our approach is promising in solving the abstractive summarization task.