As we know, computing the authority (or hub) score of HITS ranking method, means to use the following matrix equation:
$$ \textbf{a}^{k}=A^T A\textbf{a}^{(k-1)} $$
and apply the power iteration method, but with significant problems: actually, AFAIK, the convergence in not guaranteed, for the matrix $A^T A$ is sometimes not irreducible (so we cannot use Perron-Frobenius theorem and the power method may converge to nonunique solutions).
Now, I'm wondering: why not apply the SVD to $A$, in order to find the dominant eigenvector(s) of $A^T A$? Do you notice any possible issue with this approach? Will the computational cost be prohibitive?
svds
, notsvd
) will yield better results than a "vanilla" power iteration. I wanted to mention it because the only answer up to now points in the opposite direction (and refers to non-sparsesvd
only). $\endgroup$