Collaboratively Improving Topic Discovery and Word Embeddings by Coordinating Global and Local Contexts

Abstract

A text corpus typically contains two types of context information -- global context and local context. Global context carries topical information which can be utilized by topic models to discover topic structures from the text corpus, while local context can train word embeddings to capture semantic regularities reflected in the text corpus. This encourages… (More)
DOI: 10.1145/3097983.3098009

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