Skeleton Trees for the Efficient Decoding of Huffman Encoded Texts

@article{Klein2000SkeletonTF,
  title={Skeleton Trees for the Efficient Decoding of Huffman Encoded Texts},
  author={Shmuel Tomi Klein},
  journal={Information Retrieval},
  year={2000},
  volume={3},
  pages={7-23}
}
A new data structure is investigated, which allows fast decoding of texts encoded by canonical Huffman codes. The storage requirements are much lower than for conventional Huffman trees, O(log2 n) for trees of depth O(log n), and decoding is faster, because a part of the bit-comparisons necessary for the decoding may be saved. Empirical results on large real-life distributions show a reduction of up to 50% and more in the number of bit operations. The basic idea is then generalized, yielding… CONTINUE READING
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  • Empirical results on large real-life distributions show a reduction of up to 50% and more in the number of bit operations.

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