  SimRank, proposed by Jeh and Widom, provides a good similarity measure that
has been successfully used in numerous applications. While there are many
algorithms proposed for computing SimRank, their computational costs are very
high. In this paper, we propose a new computational technique, "SimRank
linearization," for computing SimRank, which converts the SimRank problem to a
linear equation problem. By using this technique, we can solve many SimRank
problems, such as single-pair compuation, single-source computation, all-pairs
computation, top k searching, and similarity join problems, efficiently.
