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Simple, Fast, and Efficient Natural Language Adaptive Compression

机译:简单,快速和高效的自然语言自适应压缩

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摘要

One of the most successful natural language compression methods is word-based Huffman. However, such a two-pass semi-static compressor is not well suited to many interesting real-time transmission scenarios. A one-pass adaptive variant of Huffman exists, but it is character-oriented and rather complex. In this paper we implement word-based adaptive Huffman compression, showing that it obtains very competitive compression ratios. Then, we show how End-Tagged Dense Code, an alternative to word-based Huffman, can be turned into a faster and much simpler adaptive compression method which obtains almost the same compression ratios.
机译:基于单词的霍夫曼是最成功的自然语言压缩方法之一。但是,这样的两遍半静态压缩机不适用于许多有趣的实时传输方案。存在霍夫曼的单程自适应变体,但是它是面向字符的,并且相当复杂。在本文中,我们实现了基于单词的自适应霍夫曼压缩,表明它获得了非常有竞争力的压缩率。然后,我们展示了如何将End-Tagged Dense Code(基于单词的Huffman的替代方法)转变为一种更快,更简单的自适应压缩方法,该方法可获得几乎相同的压缩率。

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