In LDA, each topic multinomial distribution φ k is generated by a conjugate Dirichlet prior with parameter β, while each document multinomial distribution θ d is generated by a conjugate Dirichlet prior with parameter α.
θ d,k is the probability of topic k occurring in document D (i.e.