Generally speaking, the problem becomes more difficult in translingual distributional word clustering, since the sparseness of data in two languages is multiplied.
the sense-vs.-clue correlation matrix calculation method overcomes this difficulty; it calculates the correlations between senses and clues iteratively to smooth out the sparse data.