9. The method according to claim 8 , wherein the references comprise citations, each document d s having a set of citations Q d s , further comprising constructing a matrix S to denote direct relationships among the documents wherein S ls = 1  Q d s  ⁢ ⁢ for ⁢ ⁢ d l ∈ Q d s ⁢ ⁢ and ⁢ ⁢ 0 ⁢ ⁢ otherwise , where |Q d s | denotes the size of the set Q d s , and employing a generative process for generating a related document c from the respective document d s , comprising: setting l=s; choosing t˜Bernoulli(β); if t=1, choosing h˜Multinomial(S .,l ), where S .,l denotes the l-th column; setting l=h, and returning to said choosing step; and if t=0, letting c=d l , to thereby combine a Bernoulli process and a random walk on a directed graph together, where a transitive property of the citations is captured, wherein the parameter β of the Bernoulli process determines a probability that the random walk stops at a current node, and the parameter β also specifies how much of the content of the respective document is influenced from the direct or indirect citations.
8. The method according to claim 7 , wherein topic distributions at the reference level are parameterized by a K×N matrix Θ where Θ=p(z ji =l|d j ), which is to be estimated, and an M×K word probability matrix Λ, where Λ hl =p(w si h =1|t si =l), which is to be estimated.