We propose an adapted version on the random walking view of the Adsorption algorithm (Baluja et al., 2008) by updating the following formula until L converges, where M is the semantic transition matrix built from G; D = Diag[log tf (t)] is a diagonal matrix of log frequencies, which is designed to assign higher "confidence" scores to more frequent seeds; and α is a balancing parameter.
when α = 0, we can set the prior knowledge I without V c to L 0 so that only lexical semantic clue is used; otherwise if α = 1, only contextual semantic clue is used.