Embedding-Driven Multi-Dimensional Topic Mining and Text Analysis

People nowadays are immersed in a wealth of text data, ranging from news articles, to social media, academic publications, advertisements, and economic reports. A grand challenge of data mining is to develop effective, scalable and weakly-supervised methods for extracting actionable structures and knowledge from massive text data. Without requiring extensive and corpus-specific human annotations, these methods will satisfy people's diverse applications and needs for comprehending and making good use of large-scale corpora.