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1 Ergebnisse
1
Enhancing Topic Interpretability for Neural Topic Modeling ..:
, In:
2024 IEEE 40th International Conference on Data Engineering (ICDE)
,
Gao, Xin
;
Lin, Yang
;
Li, Ruiqing
... - p. 584-597 , 2024
Link:
https://doi.org/10.1109/ICDE60146.2024.00051
RT T1 <cTitle>2024 IEEE 40th International Conference on Data Engineering (ICDE)</cTitle>: T1 <Title>Enhancing Topic Interpretability for Neural Topic Modeling Through Topic-Wise Contrastive Learning</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10597746&Exemplar=1&LAN=DE A1 Gao, Xin A1 Lin, Yang A1 Li, Ruiqing A1 Wang, Yasha A1 Chu, Xu A1 Ma, Xinyu A1 Yu, Hailong YR 2024 SN 2375-026X K1 Training K1 Measurement K1 Contrastive learning K1 Coherence K1 Knowledge discovery K1 Data engineering K1 Data models K1 Data mining K1 Topic modeling SP 584 OP 597 LK http://dx.doi.org/https://doi.org/10.1109/ICDE60146.2024.00051 DO https://doi.org/10.1109/ICDE60146.2024.00051 SF ELIB - SuUB Bremen
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