We also assume that the keywords are conditionally independent of each other: Since I and D are represented jointly as the concatenation of textual and visual terms, we may intuitively simplify the problem and use the mixed document representation d Mix directly in estimating the conditional probabilities P(w t |I, D): Substituting Equation (6) into (5) yields: As mentioned earlier, we assume that the image and its associated text are generated by a mixture of latent topics which we infer using LDA.
we select the number of topics K and apply the LDA algorithm to a corpus consisting of documents {d Mix } in order to obtain the multimodal word distributions over topics P(w|z 1:K ), and the estimated posterior of the topic proportions over documents P(z 1:K |d Mix ).