@inproceedings{vhatkar-etal-2020-knowledge,
title = "Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples",
author = "Vhatkar, Amit and
Bhattacharyya, Pushpak and
Arya, Kavi",
editor = "El-Haj, Dr Mahmoud and
Athanasakou, Dr Vasiliki and
Ferradans, Dr Sira and
Salzedo, Dr Catherine and
Elhag, Dr Ans and
Bouamor, Dr Houda and
Litvak, Dr Marina and
Rayson, Dr Paul and
Giannakopoulos, Dr George and
Pittaras, Nikiforos",
booktitle = "Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "COLING",
url = "https://aclanthology.org/2020.fnp-1.22",
pages = "130--136",
abstract = "In our research work, we represent the content of the sentence in graphical form after extracting triples from the sentences. In this paper, we will discuss novel methods to generate an extractive summary by scoring the triples. Our work has also touched upon sequence-to-sequence encoding of the content of the sentence, to classify it as a summary or a non-summary sentence. Our findings help to decide the nature of the sentences forming the summary and the length of the system generated summary as compared to the length of the reference summary.",
}
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%0 Conference Proceedings
%T Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples
%A Vhatkar, Amit
%A Bhattacharyya, Pushpak
%A Arya, Kavi
%Y El-Haj, Dr Mahmoud
%Y Athanasakou, Dr Vasiliki
%Y Ferradans, Dr Sira
%Y Salzedo, Dr Catherine
%Y Elhag, Dr Ans
%Y Bouamor, Dr Houda
%Y Litvak, Dr Marina
%Y Rayson, Dr Paul
%Y Giannakopoulos, Dr George
%Y Pittaras, Nikiforos
%S Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation
%D 2020
%8 December
%I COLING
%C Barcelona, Spain (Online)
%F vhatkar-etal-2020-knowledge
%X In our research work, we represent the content of the sentence in graphical form after extracting triples from the sentences. In this paper, we will discuss novel methods to generate an extractive summary by scoring the triples. Our work has also touched upon sequence-to-sequence encoding of the content of the sentence, to classify it as a summary or a non-summary sentence. Our findings help to decide the nature of the sentences forming the summary and the length of the system generated summary as compared to the length of the reference summary.
%U https://aclanthology.org/2020.fnp-1.22
%P 130-136
Markdown (Informal)
[Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples](https://aclanthology.org/2020.fnp-1.22) (Vhatkar et al., FNP 2020)
ACL