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Topic Discovery in Text

We develop probabilistic topic models for discovering thematic structure and extracting topics from text. Work carried out in this area including joint topic and topic-specific embedding learning, topic disentanglement, neural topic models with adversarial learning, joint topic and discourse detection in microblog conversations, viewpoint and perspective detection in tweets and political debates.


Zheng Fang, Lin Gui, Gabriele Pergola, Runcong Zhao, Lixing Zhu