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@inproceedings{1489716,
author = {Gallo, Matej and Popelínský, Lubomír and Vaculík, Karel},
address = {Košice},
booktitle = {ITAT 2018 Proceedings,},
editor = {S. Krajči},
keywords = {text summarization; dynamic graph mining},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Košice},
isbn = {978-1-72726-719-8},
pages = {28-34},
publisher = {Safarik University, Faculty of Science, Kosice, Slovakia},
title = {To text summarization by dynamic graph mining},
year = {2018}
}
TY - JOUR
ID - 1489716
AU - Gallo, Matej - Popelínský, Lubomír - Vaculík, Karel
PY - 2018
TI - To text summarization by dynamic graph mining
PB - Safarik University, Faculty of Science, Kosice, Slovakia
CY - Košice
SN - 9781727267198
KW - text summarization
KW - dynamic graph mining
N2 - We show that frequent patterns can contribute to the quality of text summarization. Here we focus on single-document extractive summarization in English. Performance of the frequent patterns based model obtained with DGRMiner yields the most relevant sentences of all compared methods. Two out of three proposed methods outperform other methods if compared on ROUGE data.
ER -
GALLO, Matej, Lubomír POPELÍNSKÝ a Karel VACULÍK. To text summarization by dynamic graph mining. Online. In S. Krajči. \textit{ITAT 2018 Proceedings,}. Košice: Safarik University, Faculty of Science, Kosice, Slovakia, 2018, s.~28-34. ISBN~978-1-72726-719-8.
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