Adjusting BERT’s Pooling Layer for Large-Scale Multi-Label Text Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43959359" target="_blank" >RIV/49777513:23520/20:43959359 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-58323-1_23" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-58323-1_23</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-58323-1_23" target="_blank" >10.1007/978-3-030-58323-1_23</a>
Alternative languages
Result language
angličtina
Original language name
Adjusting BERT’s Pooling Layer for Large-Scale Multi-Label Text Classification
Original language description
In this paper, we present our experiments with BERT models in the task of Large-scale Multi-label Text Classification (LMTC). In the LMTC task, each text document can have multiple class labels, while the total number of classes is in the order of thousands. We propose a pooling layer architecture on top of BERT models, which improves the quality of classification by using information from the standard [CLS] token in combination with pooled sequence output. We demonstrate the improvements on Wikipedia datasets in three different languages using public pre-trained BERT models.
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
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/DG18P02OVV016" target="_blank" >DG18P02OVV016: Development of the centralized interface for the web content and social networks data mining.</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Text, Speech, and Dialogue 23rd International Conference, TSD 2020, Brno, Czech Republic, September 8-11, 2020, Proceedings
ISBN
978-3-030-58322-4
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
8
Pages from-to
214-221
Publisher name
Springer
Place of publication
Cham
Event location
Brno, Česká republika
Event date
Sep 8, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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