P@1, P@3, P@5, and F1 values of different residual block numbers in AAPD and EUR-LEX datasets.

P@1, P@3, P@5, and F1 values of different residual block numbers in AAPD and EUR-LEX datasets.

<p>P@1, P@3, P@5, and F1 values of different residual block numbers in AAPD and EUR-LEX datasets.</p>

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Bibliographic Details
Main Author: Ling Yuan (374505) (author)
Other Authors: Xinyi Xu (505530) (author), Ping Sun (59933) (author), Hai ping Yu (19762226) (author), Yin Zhen Wei (19762229) (author), Jun jie Zhou (19762232) (author)
Published: 2024
Subjects:
Biotechnology
Infectious Diseases
Computational Biology
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
weight factor based
superior outcomes demonstrate
natural language processing
modulation function based
discriminative text representation
extreme datasets eur
correlation network based
learning label correlations
xlink "> multi
label attention mechanism
label text classification
enhance classification performance
proposed model employs
label text
label attention
classification results
proposed model
extreme multi
correlation networks
label distribution
label data
vast collection
suboptimal method
results indicate
prediction probability
paper proposes
extensive experiments
crucial task
classifying multi
challenging due
best method
art methods
achieve optimal
aapd dataset
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