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I have googled but find no results.

Text-to-(word)set generation or sequence-to-(token)set generation.

For example, input a text and then output the tags for this text:

'Peter is studying English' --> {'good behavior','person','doing something'}

Thank you!

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    $\begingroup$ This sounds as either 1) a funky text summarization problem or 2) a multi-class classification problem (where you just don't have a dataset for it yet). $\endgroup$ – BrunoGL Dec 10 '19 at 18:30
  • $\begingroup$ Also can consider semantic parsing methods. $\endgroup$ – 不是phd的phd Dec 26 '19 at 7:21
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Check out these papers below and google keywords: Multi-label Classification.

X-BERT: eXtreme Multi-label Text Classification with BERT
HAXMLNet: Hierarchical Attention Network for Extreme Multi-Label Text Classification
SGM: Sequence Generation Model for Multi-label Classification
Ranking-Based Autoencoder for Extreme Multi-label Classification
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification

Also check out the code below:

https://github.com/chenyuntc/PyTorchText

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