Extract with Order for Coherent Multi-Document Summarization

Mir Tafseer Nayeem, Yllias Chali


Abstract
In this work, we aim at developing an extractive summarizer in the multi-document setting. We implement a rank based sentence selection using continuous vector representations along with key-phrases. Furthermore, we propose a model to tackle summary coherence for increasing readability. We conduct experiments on the Document Understanding Conference (DUC) 2004 datasets using ROUGE toolkit. Our experiments demonstrate that the methods bring significant improvements over the state of the art methods in terms of informativity and coherence.
Anthology ID:
W17-2407
Volume:
Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venues:
TextGraphs | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
51–56
Language:
URL:
https://www.aclweb.org/anthology/W17-2407
DOI:
10.18653/v1/W17-2407
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-2407.pdf