If you are storing integers which are close together (eg: 1, 3 ,4, 5, 9, 10 etc... ) rather than some random 32 bit integers (982346..., 3487623412.., etc) you can do one thing:
Find the differences between the adjacent numbers which would be like 2,1,1,4,1... etc.(in our example) and then Huffman encode this numbers.
I don't think Huffman encoding will work if you directly apply them to the original list of numbers you have.
But if you have a sorted list of near-by numbers, the odds are good that you will get a very good compression ratio by doing Huffman encoding of the number differences, may be better ratio than using the LZW algorithm used in the Zip libraries.
Anyway thanks for posting this interesting question.
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