GLTM: A Global and Local Word Embedding-Based Topic Model for Short Texts
Short texts have become a kind of prevalent source of information, and discovering topical information from short text collections is valuable for many applications.Due to the length limitation, conventional topic models based on document-level word co-occurrence information often fail to distill semantically coherent topics from short text collect