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        <title>Extract with Order for Coherent Multi-Document Summarization</title>
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    <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.</abstract>
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%0 Conference Proceedings
%T Extract with Order for Coherent Multi-Document Summarization
%A Nayeem, Mir Tafseer
%A Chali, Yllias
%Y Riedl, Martin
%Y Somasundaran, Swapna
%Y Glavaš, Goran
%Y Hovy, Eduard
%S Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F nayeem-chali-2017-extract
%X 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.
%R 10.18653/v1/W17-2407
%U https://aclanthology.org/W17-2407
%U https://doi.org/10.18653/v1/W17-2407
%P 51-56

Markdown (Informal)

[Extract with Order for Coherent Multi-Document Summarization](https://aclanthology.org/W17-2407) (Nayeem & Chali, TextGraphs 2017)

• Extract with Order for Coherent Multi-Document Summarization (Nayeem & Chali, TextGraphs 2017)

ACL

• Mir Tafseer Nayeem and Yllias Chali. 2017. Extract with Order for Coherent Multi-Document Summarization. In Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing, pages 51–56, Vancouver, Canada. Association for Computational Linguistics.