Papers with keyphrase extraction models

2 papers
AutoNLU: An On-demand Cloud-based Natural Language Understanding System for Enterprises (2020.aacl-demo)

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Challenge: AutoNLU is an on-demand cloud-based system that enables users to create and edit datasets and train and test different state-of-the-art NLU models.
Approach: They introduce an on-demand cloud-based system that provides an easy-to-use interface . they build powerful keyphrase extraction models that achieve state-of-the-art results .
Outcome: The proposed model achieves state-of-the-art on two public benchmarks and is easy to use and use.
Using Human Attention to Extract Keyphrase from Microblog Post (P19-1)

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Challenge: Existing studies on keyphrase extraction neglect human reading behavior during keyphrase annotating.
Approach: They propose to integrate human attention into keyphrase extraction models by an attention mechanism and combine it with neural network models.
Outcome: The proposed models improve on two Twitter datasets.

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