Abstractive summarization: An overview of the state of the art

作者：

Highlights：

• AMR Graphs are based upon PropBanks which limits them.

• Deep Learning Models capture both the syntactic and semantic structure.

• Requirement of large data set limits the use of Deep Learning Models.

• Need of generalized framework for abstractive summaries is the need of time.

摘要

•AMR Graphs are based upon PropBanks which limits them.•Deep Learning Models capture both the syntactic and semantic structure.•Requirement of large data set limits the use of Deep Learning Models.•Need of generalized framework for abstractive summaries is the need of time.

论文关键词：Abstractive summarization,Concept finding,Semantic-Based summarization,Ontology-Based summarization,Deep learning

论文评审过程：Received 3 September 2018, Revised 28 October 2018, Accepted 6 December 2018, Available online 7 December 2018, Version of Record 14 December 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.011