Topic Words Extraction Method Based on LDA Model
Wanlong Li · 2010
Latent Dirichlet Allocation(LDA) is presented to express the distributed probability of words.The topic keywords are extracted according to Shannon information.Words which are not distinctly in the analyzed text can be included to express the topics with the help of word clustering of background and topic words association.The topic meaning is attempted to dig out.Fast Gibbs is used to estimate the parameters.Experiments show that Fast Gibbs is 5 times faster than Gibbs and the precision is satisfactory,which shows the approach is efficient.