Just some odd thoughts rather than a clear strategy. Say you have 75 attributes and 500 objects.

1. Define a measure of distance between any pair of objects, e.g. 75 minus the number of common objects or 1 over the number of common objects.
2. Calculate all distances between pairs. This gives you 250*499 distances.
3. Apply some kind of clustering algorithm, e.g. nearest neighbors or something. These should be available on CPAN.

Playing with distance measures and clustering algorithms (and their parameters) will lead you to a number of different solutions.