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of 35
pro vyhledávání: '"Petrak, Johann"'
Autor:
Petrak, Johann, Krenn, Brigitte
This paper presents work on detecting misogyny in the comments of a large Austrian German language newspaper forum. We describe the creation of a corpus of 6600 comments which were annotated with 5 levels of misogyny. The forum moderators were involv
Externí odkaz:
http://arxiv.org/abs/2211.17163
Publikováno v:
PLOS ONE 2021
The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide, and brought a new major challenge to government responses worldwide. Not only is disinformation creating confusion about medical scie
Externí odkaz:
http://arxiv.org/abs/2006.03354
In the sentence classification task, context formed from sentences adjacent to the sentence being classified can provide important information for classification. This context is, however, often ignored. Where methods do make use of context, only sma
Externí odkaz:
http://arxiv.org/abs/1809.00934
Autor:
Derczynski, Leon, Maynard, Diana, Rizzo, Giuseppe, van Erp, Marieke, Gorrell, Genevieve, Troncy, Raphaël, Petrak, Johann, Bontcheva, Kalina
Publikováno v:
Information Processing & Management 51 (2), 32-49, 2014
Applying natural language processing for mining and intelligent information access to tweets (a form of microblog) is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new cha
Externí odkaz:
http://arxiv.org/abs/1410.7182
Publikováno v:
In Procedia Computer Science 2018 137:102-108
Autor:
Derczynski, Leon, Maynard, Diana, Rizzo, Giuseppe, van Erp, Marieke, Gorrell, Genevieve, Troncy, Raphaël, Petrak, Johann, Bontcheva, Kalina
Publikováno v:
In Information Processing and Management March 2015 51(2):32-49
Autor:
Song, Xingyi1 (AUTHOR) x.song@sheffield.ac.uk, Petrak, Johann1,2 (AUTHOR), Jiang, Ye1 (AUTHOR), Singh, Iknoor1,3 (AUTHOR), Maynard, Diana1 (AUTHOR), Bontcheva, Kalina1 (AUTHOR)
Publikováno v:
PLoS ONE. 2/18/2021, Vol. 16 Issue 2, p1-22. 22p.
Akademický článek
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Automatic Term Extraction is a fundamental Natural Language Processing task often used in many knowledge acquisition processes. It is a challenging NLP task due to its high domain dependence: no existing methods can consistently outperform others in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36c2df1e51f1e910e1949e94cd23731e