Benchmark dataset properties.

<div><p>Multi-Label Text Classification (MLTC) is a crucial task in natural language processing. Compared to single-label text classification, MLTC is more challenging due to its vast collection of labels which include extracting local semantic information, learning label correlations, a...

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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 &# 8764
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Benchmark dataset properties.

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