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Mining Semantic Subspaces to Express Discipline-Specific Si..:
, In:
Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020
,
Wawrzinek, Janus
;
Pinto, José María González
;
Balke, Wolf-Tilo
- p. 309-318 , 2020
Link:
https://dl.acm.org/doi/10.1145/3383583.3398523
RT T1 <cTitle>Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020</cTitle>: T1 <Title>Mining Semantic Subspaces to Express Discipline-Specific Similarities</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3398523&Exemplar=1&LAN=DE A1 Wawrzinek, Janus A1 Pinto, José María González A1 Balke, Wolf-Tilo PB ACM YR 2020 K1 medical digital libraries K1 neural language models K1 pharmaceutical entities K1 semantic subspaces K1 word embeddings K1 Information systems K1 Information systems applications K1 Data mining K1 Information retrieval K1 Document representation K1 Content analysis and feature selection K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Learning latent representations SP 309 OP 318 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3383583.3398523 DO https://dl.acm.org/doi/10.1145/3383583.3398523 SF ELIB - SuUB Bremen
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