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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.
This article explains the concept of a prefix tree (Trie), demonstrates how to build and use it for prefix searches, insertions, and deletions, and provides a complete Java implementation with detailed examples and visual illustrations.
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.
This article introduces common graph concepts and several advanced string‑matching algorithms—including Brute‑Force, Rabin‑Karp, KMP, Boyer‑Moore, AC automaton, Trie, and Double‑Array Trie—explaining their principles, implementations, complexity analyses, and typical application scenarios for search systems.
This article explains how to use a trie (prefix tree) to efficiently filter sensitive words in a text, covering the basic concepts, construction steps, traversal algorithm, complexity analysis, and a Java implementation using HashMap.
This article presents SlimTrie, a trie‑based indexing structure that dramatically reduces memory consumption while maintaining fast query speeds, detailing its design, compression techniques, implementation steps, memory analysis, and performance comparisons with map and B‑Tree structures for large‑scale storage systems.
The discussion outlines practical anti‑spam strategies—including text length limits, keyword replacement, trie‑based data structures, AC automata, Bayesian and vector‑similarity algorithms, and PHP extensions such as libdatrie—while also sharing performance metrics and resource links for implementing robust content filtering systems.