Longest Common Extensions with Recompression

T. I.
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引用次数: 30

Abstract

Given two positions i and j in a string T of length N, a longest common extension (LCE) query asks for the length of the longest common prefix between suffixes beginning at i and j. A compressed LCE data structure stores T in a compressed form while supporting fast LCE queries. In this article we show that the recompression technique is a powerful tool for compressed LCE data structures. We present a new compressed LCE data structure of size O(z lg (N/z)) that supports LCE queries in O(lg N) time, where z is the size of Lempel-Ziv 77 factorization without self-reference of T. Given T as an uncompressed form, we show how to build our data structure in O(N) time and space. Given T as a grammar compressed form, i.e., a straight-line program of size n generating T, we show how to build our data structure in O(n lg (N/n)) time and O(n + z lg (N/z)) space. Our algorithms are deterministic and always return correct answers.
带重压缩的最长公共扩展
在长度为N的字符串T中给定两个位置i和j,最长公共扩展(LCE)查询请求以i和j开头的后缀之间最长公共前缀的长度。压缩LCE数据结构以压缩形式存储T,同时支持快速LCE查询。在本文中,我们将展示再压缩技术是压缩LCE数据结构的强大工具。我们提出了一个新的压缩LCE数据结构,其大小为O(z lg (N/z)),支持在O(lg N)时间内进行LCE查询,其中z是没有自引用T的Lempel-Ziv 77分解的大小。给定T是未压缩的形式,我们展示了如何在O(N)时间和空间内构建我们的数据结构。给定T作为语法压缩形式,即大小为n的直线程序生成T,我们展示如何在O(n lg (n /n))时间和O(n + z lg (n /z))空间中构建我们的数据结构。我们的算法是确定性的,总是返回正确的答案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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