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@inproceedings{1809765,
author = {Suchomel, Vít and Kraus, Jan},
address = {Brno},
booktitle = {Recent Advances in Slavonic Natural Language Processing (RASLAN 2021)},
editor = {Horák, Rychlý, Rambousek},
keywords = {Web crawling; Web spam; Text corpus; Text processing},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Brno},
isbn = {978-80-263-1670-1},
pages = {167-175},
publisher = {Tribun EU},
title = {Website Properties in Relation to the Quality of Text Extracted for Web Corpora},
url = {https://nlp.fi.muni.cz/raslan/2021/paper19.pdf},
year = {2021}
}
TY - JOUR
ID - 1809765
AU - Suchomel, Vít - Kraus, Jan
PY - 2021
TI - Website Properties in Relation to the Quality of Text Extracted for Web Corpora
PB - Tribun EU
CY - Brno
SN - 9788026316701
KW - Web crawling
KW - Web spam
KW - Text corpus
KW - Text processing
UR - https://nlp.fi.muni.cz/raslan/2021/paper19.pdf
N2 - In this paper we present our research concerning the relation between two properties of websites and the quality of the text extracted from a website in the context of crawling the web and building large web corpora. A manual classification of text quality of 18 thousand websites from 21 European languages was used to verify our assumption that certain web domain properties can be used to identify potential sources of bad quality content. The first property is the distance of a web domain from the seed domains in a web crawl. The second property studied in this work is the length of the website name. Although these properties were recommended to help identify good quality websites in our previous work, in this paper we show there is only a small difference between the quality of text-rich web domains with various seed distances or name lengths. This conclusion holds for the post-crawling text processing when starting the web crawl with a large amount of seed domains.
ER -
SUCHOMEL, Vít a Jan KRAUS. Website Properties in Relation to the Quality of Text Extracted for Web Corpora. In Horák, Rychlý, Rambousek. \textit{Recent Advances in Slavonic Natural Language Processing (RASLAN 2021)}. Brno: Tribun EU, 2021, s.~167-175. ISBN~978-80-263-1670-1.
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