Papers with neural-based approach

3 papers
Named Entity Recognition for Social Media Texts with Semantic Augmentation (2020.emnlp-main)

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Challenge: Existing approaches for named entity recognition suffer from data sparsity problems when conducted on short and informal texts.
Approach: They propose a neural-based approach to named entity recognition for social media texts . they obtain augmented semantic information from a large-scale corpus and encode it .
Outcome: The proposed approach outperforms existing approaches on three social media datasets.
Continuous Learning for Large-scale Personalized Domain Classification (N19-1)

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Challenge: Domain classification is the task to map spoken language utterances to one of the natural language understanding domains in intelligent personal digital assistants.
Approach: They propose a neural-based approach for continuous domain adaption with normalization and regularization to accommodate new domains.
Outcome: The proposed approach outperforms baseline methods on accommodated new domains and existing known domains by a large margin.
RoBERT2VecTM: A Novel Approach for Topic Extraction in Islamic Studies (2024.findings-emnlp)

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Challenge: a new approach to investigate “Hadith” texts presents challenges due to the complexity of Arabic . a novel neural-based approach to analyze “Matn” topics outperforms traditional NLP models .
Approach: They propose a novel approach to analyze Arabic “Hadith” texts using the Contextualized Topic Model.
Outcome: The proposed approach outperforms state-of-the-art models by generating more coherent topics in Arabic.

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