Deep Learning for Extreme Multi-label Text Classification

@inproceedings{Liu2017DeepLF,
  title={Deep Learning for Extreme Multi-label Text Classification},
  author={Jingzhou Liu and Wei-Cheng Chang and Yuexin Wu and Yiming Yang},
  booktitle={SIGIR},
  year={2017}
}
Extreme multi-label text classification (XMTC) refers to the problem of assigning to each document its most relevant subset of class labels from an extremely large label collection, where the number of labels could reach hundreds of thousands or millions. The huge label space raises research challenges such as data sparsity and scalability. Significant progress has been made in recent years by the development of new machine learning methods, such as tree induction with large-margin partitions… CONTINUE READING
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