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Faster entropy-bounded compressed suffix trees

机译:更快的以熵为界的压缩后缀树

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摘要

Suffix trees are among the most important data structures in stringology, with a number of applications in flourishing areas like bioinformatics. Their main problem is space usage, which has triggered much research striving for compressed representations that are still functional. A smaller suffix tree representation could fit in a faster memory, outweighing by far the theoretical slowdown brought by the space reduction. We present a novel compressed suffix tree, which is the first achieving at the same time sublogarithmic complexity for the operations, and space usage that asymptotically goes to zero as the entropy of the text does. The main ideas in our development are compressing the longest common prefix information, totally getting rid of the suffix tree topology, and expressing all the suffix tree operations using range minimum queries and a novel primitive called next/previous smaller value in a sequence. Our solutions to those operations are of independent interest.
机译:后缀树是字符串学中最重要的数据结构之一,在诸如生物信息学等蓬勃发展的领域中有许多应用。他们的主要问题是空间的使用,这引发了许多研究,要求仍可使用的压缩表示形式。较小的后缀树表示形式可能适合更快的内存,远远超过了空间减少带来的理论上的放缓。我们提出了一种新颖的压缩后缀树,它是同时实现次对数复杂度运算的第一个树,并且空间使用率随着文本的熵渐近地变为零。我们开发的主要思想是压缩最长的公共前缀信息,完全摆脱后缀树拓扑,并使用范围最小查询和一种新颖的原语(称为序列的下一个/上一个较小的值)来表示所有后缀树操作。我们对这些运营的解决方案具有独立利益。

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