String Indexing with Compressed Patterns

IF 0.9 3区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Philip Bille, Inge Li Gørtz, Teresa Anna Steiner
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引用次数: 0

Abstract

Given a string S of length n, the classic string indexing problem is to preprocess S into a compact data structure that supports efficient subsequent pattern queries. In this paper we consider the basic variant where the pattern is given in compressed form and the goal is to achieve query time that is fast in terms of the compressed size of the pattern. This captures the common client-server scenario, where a client submits a query and communicates it in compressed form to a server. Instead of the server decompressing the query before processing it, we consider how to efficiently process the compressed query directly. Our main result is a novel linear space data structure that achieves near-optimal query time for patterns compressed with the classic Lempel-Ziv 1977 (LZ77) compression scheme. Along the way we develop several data structural techniques of independent interest, including a novel data structure that compactly encodes all LZ77 compressed suffixes of a string in linear space and a general decomposition of tries that reduces the search time from logarithmic in the size of the trie to logarithmic in the length of the pattern.

使用压缩模式的字符串索引
给定一个长度为n的字符串S,经典的字符串索引问题是将S预处理成一个紧凑的数据结构,以支持高效的后续模式查询。在本文中,我们考虑了以压缩形式给出模式的基本变体,其目标是在模式的压缩大小方面实现更快的查询时间。这捕获了常见的客户机-服务器场景,其中客户机提交查询并以压缩形式将其传递给服务器。我们考虑如何有效地直接处理压缩后的查询,而不是服务器在处理查询之前对其进行解压缩。我们的主要成果是一种新的线性空间数据结构,对于使用经典的Lempel-Ziv 1977 (LZ77)压缩方案压缩的模式,它实现了近乎最优的查询时间。在此过程中,我们开发了几种独立感兴趣的数据结构技术,包括一种新颖的数据结构,它可以在线性空间中紧凑地编码字符串的所有LZ77压缩后缀,以及一种通用的尝试分解,它可以将搜索时间从尝试大小的对数减少到模式长度的对数。
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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来源期刊
ACM Transactions on Algorithms
ACM Transactions on Algorithms COMPUTER SCIENCE, THEORY & METHODS-MATHEMATICS, APPLIED
CiteScore
3.30
自引率
0.00%
发文量
50
审稿时长
6-12 weeks
期刊介绍: ACM Transactions on Algorithms welcomes submissions of original research of the highest quality dealing with algorithms that are inherently discrete and finite, and having mathematical content in a natural way, either in the objective or in the analysis. Most welcome are new algorithms and data structures, new and improved analyses, and complexity results. Specific areas of computation covered by the journal include combinatorial searches and objects; counting; discrete optimization and approximation; randomization and quantum computation; parallel and distributed computation; algorithms for graphs, geometry, arithmetic, number theory, strings; on-line analysis; cryptography; coding; data compression; learning algorithms; methods of algorithmic analysis; discrete algorithms for application areas such as biology, economics, game theory, communication, computer systems and architecture, hardware design, scientific computing
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