  The density-matrix renormalization group (DMRG) algorithm can be adapted to
the calculation of dynamical correlation functions in various ways which all
represent compromises between computational efficiency and physical accuracy.
In this paper we reconsider the oldest approach based on a suitable
Lanczos-generated approximate basis and implement it using matrix product
states (MPS) for the representation of the basis states. The direct use of
matrix product states combined with an ex-post reorthogonalization method
allows to avoid several shortcomings of the original approach, namely the
multi-targeting and the approximate representation of the Hamiltonian inherent
in earlier Lanczos-method implementations in the DMRG framework, and to deal
with the ghost problem of Lanczos methods, leading to a much better convergence
of the spectral weights and poles. We present results for the dynamic spin
structure factor of the spin-1/2 antiferromagnetic Heisenberg chain. A
comparison to Bethe ansatz results in the thermodynamic limit reveals that the
MPS-based Lanczos approach is much more accurate than earlier approaches at
minor additional numerical cost.
