  We develop a method allowing us to reconstruct individual tastes of customers
from a sparsely connected network of their opinions on products, services, or
each other. Two distinct phase transitions occur as the density of edges in
this network is increased: above the first - macroscopic prediction of tastes
becomes possible, while above the second - all unknown opinions can be uniquely
reconstructed. We illustrate our ideas using a simple Gaussian model, which we
study using both field-theoretical methods and numerical simulations. We point
out a potential relevance of our approach to the field of bioinformatics.
