Website Properties in Relation to the Quality of Text Extracted for Web Corpora
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F21%3A00123254" target="_blank" >RIV/00216224:14330/21:00123254 - isvavai.cz</a>
Result on the web
<a href="https://nlp.fi.muni.cz/raslan/2021/paper19.pdf" target="_blank" >https://nlp.fi.muni.cz/raslan/2021/paper19.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Website Properties in Relation to the Quality of Text Extracted for Web Corpora
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
<a href="/en/project/LM2018101" target="_blank" >LM2018101: Digital Research Infrastructure for the Language Technologies, Arts and Humanities</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Recent Advances in Slavonic Natural Language Processing (RASLAN 2021)
ISBN
9788026316701
ISSN
2336-4289
e-ISSN
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Number of pages
9
Pages from-to
167-175
Publisher name
Tribun EU
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2021
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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