Compressed double-array tries for string dictionaries supporting fast lookup

Kanda, Shigenobu; Morita, Ken; Fuketa, Masao

doi:10.1007/s10115-016-0999-8

Cited by 19 publications

(33 citation statements)

References 29 publications

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“…12,[45][46][47][48] With respect to DA dictionaries, BASE and CHECK use many bits since they are pointer-based arrays. Therefore, we will investigate efficient compression methods for BASE and CHECK in dynamic DAs.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, static tries can implement mapping keys to unique identifiers using RANK/SELECT operations. 12 Basic operations. Here, we define 3 basic dictionary operations: SEARCH, INSERT, and DELETE.…”

Section: Dictionary Implementationmentioning

confidence: 99%

“…This is because node addresses change frequently during updates. On the other hand, static tries can implement mapping keys to unique identifiers using R ank /S elect operations …”

Section: Da Trie Dictionariesmentioning

confidence: 99%

“…Most studies of static DA tries attempted to improve space efficiency and retrieval speed. [8][9][10][11][12] Static DA tries are typically used for dictionaries without frequent key updates (ie, insertions and deletions), such as Darts 13 and Darts-clone. 14 With respect to dynamic DA tries, there are 2 main objectives.…”

Section: Introductionmentioning

confidence: 99%

“…Many studies have investigated static and dynamic DA tries. Most studies of static DA tries attempted to improve space efficiency and retrieval speed . Static DA tries are typically used for dictionaries without frequent key updates (ie, insertions and deletions), such as Darts and Darts‐clone .…”

Section: Introductionmentioning

confidence: 99%

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Practical rearrangement methods for dynamic double‐array dictionaries

et al. 2017

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SummaryDouble-array structures have been widely used to implement dictionaries with string keys. Although the space efficiency of dynamic double-array dictionaries tends to decrease with key updates, we can still maintain high efficiency using existing methods. However, these methods have practical problems of time and functionality. This paper presents several efficient rearrangement methods to solve these problems.Through experiments using real-world datasets, we demonstrate that the proposed rearrangement methods are much more practical than existing methods.

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Section: Discussionmentioning

confidence: 99%

Section: Dictionary Implementationmentioning

confidence: 99%

“…This is because node addresses change frequently during updates. On the other hand, static tries can implement mapping keys to unique identifiers using R ank /S elect operations …”

Section: Da Trie Dictionariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Practical rearrangement methods for dynamic double‐array dictionaries

et al. 2017

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Engineering faster double‐array Aho–Corasick automata

Kanda¹,

Akabe²,

Oda

2023

Softw Pract Exp

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Multiple pattern matching in strings is a fundamental problem in text processing applications such as regular expressions or tokenization. This article studies efficient implementations of double-array Aho-Corasick automata (DAACs), data structures for quickly performing the multiple pattern matching. The practical performance of DAACs is improved by carefully designing the data structure, and many implementation techniques have been proposed thus far. A problem in DAACs is that comprehensive descriptions and experimental analyses on their ideas are not provided. Engineers face difficulties in implementing an efficient DAAC. In this article, we review implementation techniques for DAACs and provide a comprehensive description of them. We also propose several new techniques for further improvement. We conduct exhaustive experiments through real-world datasets and reveal the best combination of techniques to achieve a higher performance in DAACs. The best combination is different from those used in the most popular libraries of DAACs, which demonstrates that their performance can be further enhanced. On the basis of our experimental analysis, we developed a new Rust library for fast multiple pattern matching using DAACs, named Daachorse, as open-source software at https://github. com/daac-tools/daachorse. Experiments demonstrate that Daachorse outperforms other AC-automaton implementations, indicating its suitability as a fast alternative for multiple pattern matching in many applications.

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