71 lines
2.9 KiB
Markdown
71 lines
2.9 KiB
Markdown
Aho-Corasick
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============
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Introduction
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------------
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Nowadays most free-text searching is based on Lucene-like approaches, where the search text is parsed into its
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various components. For every keyword a lookup is done to see where it occurs. When looking for a couple of keywords
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this approach is great. But what about it if you are not looking for just a couple of keywords, but a 100,000 of
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them? Like, for example, checking against a dictionary?
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This is where the Aho-Corasick algorithm shines. Instead of chopping up the search text, it uses all the keywords
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to build up a construct called a [Trie](http://en.wikipedia.org/wiki/Trie). There are three crucial components
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to Aho-Corasick:
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* goto
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* fail
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* output
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Every character encountered is presented to a state object within the *goto* structure. If there is a matching state,
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that will be elevated to the new current state.
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However, if there is no matching state, the algorithm will signal a *fail* and fall back to states with less depth
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(ie, a match less long) and proceed from there, until it found a matching state, or it has reached the root state.
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Whenever a state is reached that matches an entire keyword, it is emitted to an *output* set which can be read after
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the entire scan has completed.
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The beauty of the algorithm is that it is O(n). No matter how many keywords you have, or how big the search text is,
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the performance will decline in a linear way.
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Some examples you could use the Aho-Corasick algorithm for:
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* looking for certain words in texts in order to URL link or emphasize them
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* adding semantics to plain text
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* checking against a dictionary to see if syntactic errors were made
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This library is the Java implementation of the afore-mentioned Aho-Corasick algorithm for efficient string matching.
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The algorithm is explained in great detail in the white paper written by
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Aho and Corasick: ftp://163.13.200.222/assistant/bearhero/prog/%A8%E4%A5%A6/ac_bm.pdf
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Usage
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-----
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Setting up the Trie is a piece of cake:
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```java
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Trie trie = new Trie();
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trie.addKeyword("hers");
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trie.addKeyword("his");
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trie.addKeyword("she");
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trie.addKeyword("he");
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Collection<Emit> emits = trie.parseText("ushers");
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```
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You can now read the set. In this case it will find the following:
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* "she" at position 3
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* "he" at position 3
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* "hers" at position 5
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Note that the end-positions of the keyword match are emitted, not the start-positions!
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License
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-------
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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