Papers with lifelong collaborative model

1 papers
Lifelong Learning of Topics and Domain-Specific Word Embeddings (2021.findings-acl)

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Challenge: Existing lifelong topic models focus on indomain text streams in which each chunk only contains documents from a single domain.
Approach: They develop a lifelong collaborative model that uses non-negative matrix factorization to learn topics and domain-specific word embeddings.
Outcome: The proposed model can learn topics and domain-specific word embeddings from a lifelong collaborative model.

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