MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network

12th International Conference on Agents and Artificial Intelligence ICAART 2020 Ankit PalMuru Selvakumar and Malaikannan Sankarasubbu

In Multi-Label Text Classification (MLTC), one sample can belong to more than one class. It is observed that most MLTC tasks, there are dependencies or correlations among labels... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Document Classification AAPD MAGNET F1 69.6 # 2
Multi-Label Text Classification AAPD MAGNET F1 69.6 # 1
Text Classification RCV1 MAGNET Micro F1 88.5 # 1
Multi-Label Text Classification RCV1-v2 MAGNET Micro-F1 88.5 # 1
Document Classification Reuters-21578 MAGNET F1 89.9 # 1
Multi-Label Text Classification Reuters-21578 MAGNET Micro-F1 89.9 # 1
Multi-Label Text Classification Slashdot MAGNET Micro-F1 56.8 # 1

Methods used in the Paper


METHOD TYPE
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