Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Marián Šimko"'
Autor:
Jana Papcunová, Marcel Martončik, Denisa Fedáková, Michal Kentoš, Miroslava Bozogáňová, Ivan Srba, Robert Moro, Matúš Pikuliak, Marián Šimko, Matúš Adamkovič
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 3, Pp 2827-2842 (2021)
Abstract Hate speech should be tackled and prosecuted based on how it is operationalized. However, the existing theoretical definitions of hate speech are not sufficiently fleshed out or easily operable. To overcome this inadequacy, and with the help
Externí odkaz:
https://doaj.org/article/c546bec3c1434be8b79835c8f51b77dc
Autor:
Matúš Pikuliak, Michal Kentoš, Denisa Fedáková, Matus Adamkovic, Robert Moro, Marcel Martončik, Marián Šimko, Miroslava Bozogáňová, Ivan Srba, Jana Papcunová
Publikováno v:
Complex & Intelligent Systems.
Hate speech should be tackled and prosecuted based on how it is operationalized. However, the existing theoretical definitions of hate speech are not sufficiently fleshed out or easily operable. To overcome this inadequacy, and with the help of inter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8098148738508732cef6cfe59d01565f
https://doi.org/10.1007/s40747-021-00561-0
https://doi.org/10.1007/s40747-021-00561-0
Autor:
Samuel Pecar, Marián Šimko
Publikováno v:
Text, Speech, and Dialogue ISBN: 9783030835262
TDS
TDS
While classic aspect-based sentiment analysis typically includes three sub-tasks (aspect extraction, opinion extraction, and aspect-level sentiment classification), recent studies focus on exploring possibilities of knowledge sharing from different t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3c9d781c979e6a0dbd1513e9c67e06e
https://doi.org/10.1007/978-3-030-83527-9_23
https://doi.org/10.1007/978-3-030-83527-9_23
Autor:
Kristína Machová, Michal Kompan, Daniela Chudá, Martin Sarnovský, Mária Bieliková, Radoslav Blaho, Ivan Srba, Viera Maslej Kresnakova, Andrea Hrckova, Marián Šimko, Pavol Návrat, Ján Paralič
Publikováno v:
Towards Digital Intelligence Society ISBN: 9783030638719
While digital space is a place where users communicate increasingly, the recent threat of COVID-19 infection even more emphasised the necessity of effective and well-organised online environment. Therefore, it is nowadays, more whenever in the past,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0a01d89541cc33b9a2a81803fd24ce5
https://doi.org/10.1007/978-3-030-63872-6_1
https://doi.org/10.1007/978-3-030-63872-6_1
Publikováno v:
SemEval@COLING
Since propaganda became more common technique in news, it is very important to look for possibilities of its automatic detection. In this paper, we present neural model architecture submitted to the SemEval-2020 Task 11 competition: “Detection of P
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3478378c0043890467b069aab297678
https://doi.org/10.18653/v1/2020.semeval-1.232
https://doi.org/10.18653/v1/2020.semeval-1.232
Autor:
Matúš Pikuliak, Marián Šimko
Publikováno v:
Statistical Language and Speech Processing ISBN: 9783030594299
SLSP
SLSP
Many languages still lack the annotated training data needed for supervised learning. This issue is often addressed by using auxiliary supervision and the so called transfer learning. In this work we focus on the problem of combining two types of aux
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d8ea012b18f9593c690224538465256
https://doi.org/10.1007/978-3-030-59430-5_8
https://doi.org/10.1007/978-3-030-59430-5_8
Publikováno v:
SOFSEM 2020: Theory and Practice of Computer Science ISBN: 9783030389185
SOFSEM
SOFSEM
Automatic text generation can significantly help to ease human effort in many every-day tasks. Recent advancements in neural networks supported further research in this area and also brought significant improvement in quality of text generation. Unfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9fb11dce96f6b34ec1880bce45db216
https://doi.org/10.1007/978-3-030-38919-2_53
https://doi.org/10.1007/978-3-030-38919-2_53
Autor:
Marián Šimko, Matúš Pikuliak
Publikováno v:
Text, Speech, and Dialogue ISBN: 9783030583224
TDS
TDS
In this work we combine cross-lingual and cross-task supervision for zero-shot learning. Our main contribution is that we discovered that coupling models, i.e. models that share neither a task nor a language with the zero-shot target model, can impro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c1da0be025c13d9d9230f59bc2c036a
https://doi.org/10.1007/978-3-030-58323-1_17
https://doi.org/10.1007/978-3-030-58323-1_17
Autor:
Samuel Pecar, Marián Šimko
Publikováno v:
SMAP
We propose a method for taxonomic relationships extraction from text based on morpho-syntactic and pattern-based approach combined with utilization of distributional vectors and application of graph algorithms. We evaluated our method on the datasets
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1465aecc1c011ecffc87485200b6774
https://doi.org/10.1109/smap.2019.8864911
https://doi.org/10.1109/smap.2019.8864911
Publikováno v:
SemEval@NAACL-HLT
In this paper, we present neural model architecture submitted to the SemEval-2019 Task 9 competition: "Suggestion Mining from Online Reviews and Forums". We participated in both subtasks for domain specific and also cross-domain suggestion mining. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cc1309e41387554c093d5964f5caff1
http://arxiv.org/abs/1904.02981
http://arxiv.org/abs/1904.02981