Abstract: Most of the online LDA algorithms are based on the fixed vocabulary table currently.The vocabulary table may not often match the processed corpus in practice which has a bad effect on the precision of LDA.To solve this problem,we let the topic words distribution subject to the dirichlet process (DP) and re-deduce the model under the framework of BP algorithm.So that we can make the vocabulary table empty before the algorithm running and it can continually add new words to table.Results from the experiments show that,our new algorithm can make the vocabulary table match the corpus better and the dynamic vocabulary table makes the new algorithm achieve better performance on perplexity and PMI compared with other state-of-the-art fixed vocabulary online algorithms.

Key words: Latent dirichlet allocation,Dynamic vocabulary,Dirichlet process,Streaming process