An extremely fast implementation of Aho Corasick algorithm based on Double Array Trie structure. Its speed is 5 to 9 times of naive implementations, perhaps it's the fastest implementation so far ;-)
You may heard that Aho-Corasick algorithm is fast for parsing text with a huge dictionary, for example:
- looking for certain words in texts in order to URL link or emphasize them
- adding semantics to plain text
- checking against a dictionary to see if syntactic errors were made
But most implementation use a TreeMap<Character, State>
to store the goto structure, which costs O(lg(t))
time, t
is the largest amount of a word's common prefixes. The final complexity is O(n * lg(t))
, absolutely t > 2
, so n * lg(t) > n
. The others used a HashMap
, which wasted too much memory, and still remained slowly.
I improved it by replacing the XXXMap
to a Double Array Trie, whose time complexity is just O(1)
, thus we get a total complexity of exactly O(n)
, and take a perfect balance of time and memory. Yes, its speed is not related to the length or language or common prefix of the words of a dictionary.
This implementation has been widely used in my HanLP: Han Language Processing package. I hope it can serve as a common data structure library in projects handling text or NLP task.
Include this dependency in your POM. Be sure to check for the latest version in Maven Central.
<dependency>
<groupId>com.hankcs</groupId>
<artifactId>aho-corasick-double-array-trie</artifactId>
<version>1.0.1</version>
</dependency>
Setting up the AhoCorasickDoubleArrayTrie
is a piece of cake:
// Collect test data set
TreeMap<String, String> map = new TreeMap<String, String>();
String[] keyArray = new String[]
{
"hers",
"his",
"she",
"he"
};
for (String key : keyArray)
{
map.put(key, key);
}
// Build an AhoCorasickDoubleArrayTrie
AhoCorasickDoubleArrayTrie<String> acdat = new AhoCorasickDoubleArrayTrie<String>();
acdat.build(map);
// Test it
final String text = "uhers";
List<AhoCorasickDoubleArrayTrie<String>.Hit<String>> wordList = acdat.parseText(text);
Of course, there remains many useful methods to be discovered, feel free to try:
- Use a
Map<String, SomeObject>
to assign aSomeObject
as value to a keyword. - Store the
AhoCorasickDoubleArrayTrie
to disk by callingsave
method. - Restore the
AhoCorasickDoubleArrayTrie
from disk by callingload
method.
In other situations you probably do not need a huge wordList, then please try this:
acdat.parseText(text, new AhoCorasickDoubleArrayTrie.IHit<String>()
{
@Override
public void hit(int begin, int end, String value)
{
System.out.printf("[%d:%d]=%s\n", begin, end, value);
}
});
or a lambda function
acdat.parseText(text, (begin, end, value) -> {
System.out.printf("[%d:%d]=%s\n", begin, end, value);
});
I compared my AhoCorasickDoubleArrayTrie with robert-bor's aho-corasick, ACDAT represents for AhoCorasickDoubleArrayTrie and Naive represents for aho-corasick, the result is :
Parsing English document which contains 3409283 characters, with a dictionary of 127142 words.
Naive ACDAT
time 607 102
char/s 5616611.20 33424343.14
rate 1.00 5.95
===========================================================================
Parsing Chinese document which contains 1290573 characters, with a dictionary of 146047 words.
Naive ACDAT
time 319 35
char/s 2609156.74 23780600.00
rate 1.00 9.11
===========================================================================
In English test, AhoCorasickDoubleArrayTrie is 5 times faster. When it comes to Chinese, AhoCorasickDoubleArrayTrie is 9 times faster. This test is conducted under i7 2.0GHz, -Xms512m -Xmx512m -Xmn256m. Feel free to re-run this test in TestAhoCorasickDoubleArrayTrie, the test data is ready for you.
This project is inspired by aho-corasick and darts-clone-java. Many thanks!
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
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