  A recently introduced technique of topology sensitivity in method of moments
is extended by the possibility of adding degrees-of-freedom (reconstruct) into
underlying structure. The algebraic formulation is inversion-free, suitable for
parallelization and scales favorably with the number of unknowns. The
reconstruction completes the nearest neighbors procedure for an evaluation of
the smallest shape perturbation. The performance of the method is studied with
a greedy search over a Hamming graph representing the structure in which
initial positions are chosen from a random set. The method is shown to be
effective data mining tool for machine learning-related applications.
