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LZRR: LZ77 Parsing with Right Reference

机译:LZRR:具有正确参考的LZ77解析

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Lossless data compression has been widely studied in computer science. One of the most widely used lossless data compressions is Lempel-Ziv (LZ) 77 parsing, which achieves a high compression ratio. Bidirectional (a.k.a. macro) parsing is a lossless data compression and computes a sequence of phrases copied from another substring (target phrase) on either the left or the right position in an input string. Gagie et al. (LATIN 2018) recently showed that a large gap exists between the number of smallest bidirectional phrases of a given string and that of LZ77 phrases. In addition, finding the smallest bidirectional parse of a given text is NP-complete. Several variants of bidirectional parsing have been proposed thus far, but no prior work for bidirectional parsing has achieved high compression that is smaller than that of LZ77 phrasing for any string. In this paper, we present the first practical bidirectional parsing named LZ77 parsing with right reference (LZRR), in which the number of LZRR phrases is theoretically guaranteed to be smaller than the number of LZ77 phrases. Experimental results using benchmark strings show the number of LZRR phrases is approximately five percent smaller than that of LZ77 phrases.
机译:无损数据压缩已在计算机科学中被广泛研究。最广泛使用的无损数据压缩之一是Lempel-Ziv(LZ)77解析,它可以实现高压缩率。双向(也称为宏)解析是一种无损数据压缩,它计算从输入字符串左侧或右侧位置的另一个子字符串(目标短语)复制的短语序列。 Gagie等。 (LATIN 2018)最近表明,给定字符串的最小双向短语的数量与LZ77短语的数量之间存在很大的差距。另外,找到给定文本的最小双向解析是NP完全的。迄今为止,已经提出了几种双向解析的变体,但是对于任何双向字符串,双向解析的先前工作都没有实现比LZ77短语小的高压缩率。在本文中,我们提出了第一个实用的双向解析,称为LZ77右引用解析(LZRR),在理论上保证了LZRR短语的数量小于LZ77短语的数量。使用基准字符串的实验结果表明,LZRR短语的数量比LZ77短语的数量少大约5%。

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