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This article explains the Aho‑Corasick automaton, a classic multi‑pattern matching algorithm that builds a Trie with fail pointers to achieve linear‑time search over massive keyword sets, and demonstrates a Java implementation for highlighting keywords in HTML documents.
The article analyzes various Java string‑replacement techniques—including simple String.replace, compiled regular expressions, Aho‑Corasick automaton, and custom Trie implementations—by presenting their designs, object sizes, and benchmark results to guide developers in choosing the most efficient solution for large keyword sets.
By replacing the naïve double‑loop matcher with a Double‑Array Trie‑based Aho‑Corasick automaton and refactoring the system into a layered name‑and‑data microservice architecture that shards the keyword dictionary and rebuilds the automaton only on version changes, the real‑time keyword‑matching service reduced latency from seconds to milliseconds even at thousands of QPS.
The article describes how Vivo's content moderation platform, DiTing, uses algorithm selection—including Aho‑Corasick automaton, combination word matching, and pinyin‑based matching—to efficiently detect sensitive terms in large‑scale text streams, while addressing challenges such as homophones, multi‑character patterns, and performance constraints.
This article describes a Java‑based solution that dynamically adds brand and model hyperlinks to automotive articles by building multilingual keyword dictionaries with HanLP and employing an Aho‑Corasick Double‑Array Trie for efficient, context‑aware matching without altering the original content.