Efficient Dynamic Dictionary Matching with DAWGs and AC-automata
Diptarama Hendrian, Shunsuke Inenaga, Ryo Yoshinaka, Ayumi, Shinohara

TL;DR
This paper introduces two efficient algorithms for dynamic dictionary matching using DAWGs and AC-automata, supporting pattern insertions and deletions with optimized update and matching times.
Contribution
It presents novel algorithms that improve dynamic dictionary matching efficiency by leveraging DAWGs and AC-automata, supporting both insertions and deletions.
Findings
Supports pattern insertions in O(m log σ + log d / log log d) time
Supports pattern deletions with optimized time complexity
Achieves optimal update time for AC-automaton based methods over constant alphabets
Abstract
The dictionary matching is a task to find all occurrences of patterns in a set (called a dictionary) on a text . The Aho-Corasick-automaton (AC-automaton) is a data structure which enables us to solve the dictionary matching problem in preprocessing time and matching time, where is the total length of the patterns in , is the length of the text, is the alphabet size, and is the total number of occurrences of all the patterns in the text. The dynamic dictionary matching is a variant where patterns may dynamically be inserted into and deleted from . This problem is called semi-dynamic dictionary matching if only insertions are allowed. In this paper, we propose two efficient algorithms. For a pattern of length , our first algorithm supports insertions in time and pattern…
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