Abstractive news summarization based on event semantic link network

Li, Wei, He, Lei and Zhuge, Hai (2016). Abstractive news summarization based on event semantic link network. IN: The 26th International Conference on Computational Linguistics. Association for Computational Linguistics.

Abstract

This paper studies the abstractive multi-document summarization for event-oriented news texts through event information extraction and abstract representation. Fine-grained event mentions and semantic relations between them are extracted to build a unified and connected event semantic link network, an abstract representation of source texts. A network reduction algorithm is proposed to summarize the most salient and coherent event information. New sentences with good linguistic quality are automatically generated and selected through sentences over-generation and greedy-selection processes. Experimental results on DUC2006 and DUC2007 datasets show that our system significantly outperforms the state-of-the-art extractive and abstractive baselines under both pyramid and ROUGE evaluation metrics.

Divisions: Engineering & Applied Sciences
Engineering & Applied Sciences > Computer science
Engineering & Applied Sciences > Computer science research group
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Engineering & Applied Sciences > Polymer and advanced materials research group
Engineering & Applied Sciences > European Bioenergy Research Institute (EBRI)
Additional Information: This work is licenced under a Creative Commons Attribution 4.0 International License. License details: http:// creativecommons.org/licenses/by/4.0/
Event Title: 26th International Conference on Computational Linguistics
Event Type: Other
Event Dates: 2016-12-11 - 2016-12-16
Uncontrolled Keywords: Summarization,sematnic link network,event
Published Online Date: 2016-12-11
Authors: Li, Wei ( 0000-0003-4036-467X)
He, Lei
Zhuge, Hai

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Version: Accepted Version

License: Creative Commons Attribution

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