Semi-Manual Annotation of Topics and Genres in Web Corpora : The Cheap and Fast Way

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00127492" target="_blank" >RIV/00216224:14330/22:00127492 - isvavai.cz</a>
Result on the web
<a href="https://raslan2022.nlp-consulting.net/" target="_blank" >https://raslan2022.nlp-consulting.net/</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Semi-Manual Annotation of Topics and Genres in Web Corpora : The Cheap and Fast Way
Original language description
In this paper we present a cheap and fast semi-manual approach to annotation of topics and genres in web corpora. The main feature of our method is assigning the same topic or genre label to all web pages coming from websites most represented in the corpus. We assume that web pages within a site share the topic of the whole domain. According to the evaluation of texts coming from sites that were manually assigned a topic label, our hypothesis holds in 92 % of cases. In other words, the noise in these semi-manually labelled web pages is just 8 %. That is clean enough to train a classifier of texts from websites not seen in the process. The procedure of fast manual topic and genre labelling of web domains is described in this paper. Recommendations for training a topic or genre classifier using semi-manually labelled texts from large websites follow.
Czech name
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Czech description
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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)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022
ISBN
9788026317524
ISSN
2336-4289
e-ISSN
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Number of pages
8
Pages from-to
141-148
Publisher name
Tribun EU
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2022
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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