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hello everyone my name is kwang-soo and Iamp;#39;m happy to be here to present our recent work collaboratively improving topic discovery and word embeddings by coordinating global and local contexts mmm first let me introduce some background knowledge a text corpus usually contains two types of context information global context and local context the global context information of text corpus typically refers to the document level word co-occurrence information in other words the words in the same document and the word the local context information of a text corpus refers to its word level neighborhood the information in other words the neighborhood words of a focus word within context window and the document level global context information of global on of a text corpus carries topical information which can be utilized by topical topic models such as LBA and the POS a to discover topic structures from the text corpus and those top models usually follow the bag of word assumption and a
