Detailed Information on Publication Record
2018
To text summarization by dynamic graph mining
GALLO, Matej, Lubomír POPELÍNSKÝ and Karel VACULÍKBasic information
Original name
To text summarization by dynamic graph mining
Name in Czech
To text summarization by dynamic graph mining
Authors
GALLO, Matej (703 Slovakia, belonging to the institution), Lubomír POPELÍNSKÝ (203 Czech Republic, guarantor, belonging to the institution) and Karel VACULÍK (203 Czech Republic, belonging to the institution)
Edition
Košice, ITAT 2018 Proceedings, p. 28-34, 7 pp. 2018
Publisher
Safarik University, Faculty of Science, Kosice, Slovakia
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10200 1.2 Computer and information sciences
Country of publisher
Slovakia
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
RIV identification code
RIV/00216224:14330/18:00105832
Organization unit
Faculty of Informatics
ISBN
978-1-72726-719-8
ISSN
Keywords (in Czech)
sumarizace textu; dolování z dynamických grafů
Keywords in English
text summarization; dynamic graph mining
Změněno: 30/4/2019 07:38, RNDr. Pavel Šmerk, Ph.D.
V originále
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.
In Czech
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.
Links
| MUNI/A/0854/2017, interní kód MU |
|