Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 2021
DOI: 10.18653/v1/2021.findings-acl.202
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Lifelong Learning of Topics and Domain-Specific Word Embeddings

Abstract: Lifelong topic models mainly focus on indomain text streams in which each chunk only contains documents from a single domain. To overcome data diversity of the in-domain corpus, most of the existing methods exploit the information from limited sources in a separate and heuristic manner. In this study, we develop a lifelong collaborative model (LCM) based on non-negative matrix factorization to accurately learn topics and domain-specific word embeddings. LCM particularly investigates:(1) developing a knowledge … Show more

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