In text streaming data,documents of text stream into system continuously,and huge amount and quick update velocity of data pose great challenges for discovering and tracking topics in such text streaming. In order to handle those problems,this paper proposed a collective matrix factorization based topic discovering and tracking model. In order to deal with massive data,it partitioned the streaming data into batches,and in order to track the evolution of topics,it assumed the current topic distribution as th...
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