Papers by Merieme Bouhandi

1 papers
Cross-lingual and Cross-domain Transfer Learning for Automatic Term Extraction from Low Resource Data (2022.lrec-1)

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Challenge: Automatic Term Extraction (ATE) is a key component for domain knowledge understanding and can be used for further NLP applications.
Approach: They propose to fine-tune pre-trained BERT models for automatic Term Extraction (ATE) using cross-lingual and cross-domain transfer learning to extract single and multi-word terms.
Outcome: The proposed models can capture cross-domain and cross-lingual terminologically-marked contexts shared by terms, opening a new design-pattern for ATE.

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