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<!DOCTYPE html>
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<title>stringmetric | String metrics and phonetic algorithms for Scala</title>
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<section class="page-header">
<h1 class="project-name">stringmetric</h1>
<h2 class="project-tagline">String metrics and phonetic algorithms for Scala.</h2>
<a href="https://github.com/rockymadden/stringmetric" class="btn">View on GitHub</a>
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<section class="main-content">
<p>The library provides facilities to perform approximate string matching, measurement of string similarity/distance, indexing by word pronunciation, and sounds-like comparisons. In addition to the core library, each metric and algorithm has a command line interface.</p>
<ul>
<li>
<strong>Requirements:</strong> Scala 2.10+</li>
<li>
<strong>Documentation:</strong> <a href="http://rockymadden.com/stringmetric/scaladoc/">Scaladoc</a>
</li>
<li>
<strong>Issues:</strong> <a href="https://github.com/rockymadden/stringmetric/issues?labels=accepted%2Cenhancement&page=1&state=open">Enhancements</a>, <a href="https://github.com/rockymadden/stringmetric/issues?labels=accepted%2Cquestion&page=1&state=open">Questions</a>, <a href="https://github.com/rockymadden/stringmetric/issues?labels=accepted%2Cbug&page=1&state=open">Bugs</a>
</li>
<li>
<strong>Versioning:</strong> <a href="http://semver.org/">Semantic Versioning v2.0</a>
</li>
</ul>
<h2>
<a id="metrics-and-algorithms" class="anchor" href="#metrics-and-algorithms" aria-hidden="true"><span class="octicon octicon-link"></span></a>Metrics and algorithms</h2>
<ul>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Dice%27s_coefficient">Dice / Sorensen</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Metaphone">Double Metaphone</a></strong> (<a href="https://github.com/rockymadden/stringmetric/issues/6">Queued</a> phonetic metric and algorithm)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Hamming_distance">Hamming</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Jaccard_index">Jaccard</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Jaro-Winkler_distance">Jaro</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Jaro-Winkler_distance">Jaro-Winkler</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Metaphone">Metaphone</a></strong> (Phonetic metric and algorithm)</li>
<li>
<strong><a href="http://www.cs.cmu.edu/%7Epradeepr/papers/ijcai03.pdf">Monge-Elkan</a></strong> (<a href="https://github.com/rockymadden/stringmetric/issues/7">Queued</a> similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Match_rating_approach">Match Rating Approach</a></strong> (<a href="https://github.com/rockymadden/stringmetric/issues/8">Queued</a> phonetic metric and algorithm)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Needleman%E2%80%93Wunsch_algorithm">Needleman-Wunch</a></strong> (<a href="https://github.com/rockymadden/stringmetric/issues/9">Queued</a> similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/N-gram">N-Gram</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/New_York_State_Identification_and_Intelligence_System">NYSIIS</a></strong> (Phonetic metric and algorithm)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Overlap_coefficient">Overlap</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://xlinux.nist.gov/dads/HTML/ratcliffObershelp.html">Ratcliff-Obershelp</a></strong> (Similarity metric)</li>
<li>
<strong><a href="http://www.markcrocker.com/rexxtipsntricks/rxtt28.2.0482.html">Refined NYSIIS</a></strong> (Phonetic metric and algorithm)</li>
<li>
<strong><a href="http://ntz-develop.blogspot.com/2011/03/phonetic-algorithms.html">Refined Soundex</a></strong> (Phonetic metric and algorithm)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Tanimoto_coefficient">Tanimoto</a></strong> (<a href="https://github.com/rockymadden/stringmetric/issues/10">Queued</a> similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Tversky_index">Tversky</a></strong> (<a href="https://github.com/rockymadden/stringmetric/issues/16">Queued</a> similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Smith%E2%80%93Waterman_algorithm">Smith-Waterman</a></strong> (<a href="https://github.com/rockymadden/stringmetric/issues/11">Queued</a> similarity metric)</li>
<li>
<strong><a href="http://en.wikipedia.org/wiki/Soundex">Soundex</a></strong> (Phonetic metric and algorithm)</li>
<li>
<strong>Weighted Levenshtein</strong> (Similarity metric)</li>
</ul>
<h2>
<a id="depending-upon" class="anchor" href="#depending-upon" aria-hidden="true"><span class="octicon octicon-link"></span></a>Depending upon</h2>
<p><strong>SBT:</strong></p>
<div class="highlight highlight-scala"><pre>libraryDependencies <span class="pl-k">+</span><span class="pl-k">=</span> <span class="pl-s"><span class="pl-pds">"</span>com.rockymadden.stringmetric<span class="pl-pds">"</span></span> <span class="pl-k">%%</span> <span class="pl-s"><span class="pl-pds">"</span>stringmetric-core<span class="pl-pds">"</span></span> <span class="pl-k">%</span> <span class="pl-s"><span class="pl-pds">"</span>0.27.4<span class="pl-pds">"</span></span></pre></div>
<hr>
<p><strong>Gradle:</strong></p>
<div class="highlight highlight-groovy"><pre>compile <span class="pl-s"><span class="pl-pds">'</span>com.rockymadden.stringmetric:stringmetric-core_2.10:0.27.4<span class="pl-pds">'</span></span></pre></div>
<hr>
<p><strong>Maven:</strong></p>
<div class="highlight highlight-xml"><pre><<span class="pl-ent">dependency</span>>
<<span class="pl-ent">groupId</span>>com.rockymadden.stringmetric</<span class="pl-ent">groupId</span>>
<<span class="pl-ent">artifactId</span>>stringmetric-core_2.10</<span class="pl-ent">artifactId</span>>
<<span class="pl-ent">version</span>>0.27.4</<span class="pl-ent">version</span>>
</<span class="pl-ent">dependency</span>></pre></div>
<hr>
<h2>
<a id="similarity-package" class="anchor" href="#similarity-package" aria-hidden="true"><span class="octicon octicon-link"></span></a>Similarity package</h2>
<p>Useful for approximate string matching and measurement of string distance. Most metrics calculate the similarity of two strings as a double with a value between 0 and 1. A value of 0 being completely different and a value of 1 being completely similar.</p>
<hr>
<p><strong>Dice / Sorensen Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">DiceSorensenMetric</span>(<span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>night<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>nacht<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.6</span>
<span class="pl-en">DiceSorensenMetric</span>(<span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>context<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>contact<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.7142857142857143</span></pre></div>
<p><sup>Note you must specify the size of the n-gram you wish to use.</sup></p>
<hr>
<p><strong>Hamming Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">HammingMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>toned<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>roses<span class="pl-pds">"</span></span>) <span class="pl-c">// 3</span>
<span class="pl-en">HammingMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>1011101<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>1001001<span class="pl-pds">"</span></span>) <span class="pl-c">// 2</span></pre></div>
<p><sup>Note the exception of integers, rather than doubles, being returned.</sup></p>
<hr>
<p><strong>Jaccard Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">JaccardMetric</span>(<span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>night<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>nacht<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.3</span>
<span class="pl-en">JaccardMetric</span>(<span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>context<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>contact<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.35714285714285715</span></pre></div>
<p><sup>Note you must specify the size of the n-gram you wish to use.</sup></p>
<hr>
<p><strong>Jaro Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">JaroMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>dwayne<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>duane<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.8222222222222223</span>
<span class="pl-en">JaroMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>jones<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>johnson<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.7904761904761904</span>
<span class="pl-en">JaroMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>fvie<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>ten<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.0</span></pre></div>
<hr>
<p><strong>Jaro-Winkler Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">JaroWinklerMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>dwayne<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>duane<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.8400000000000001</span>
<span class="pl-en">JaroWinklerMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>jones<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>johnson<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.8323809523809523</span>
<span class="pl-en">JaroWinklerMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>fvie<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>ten<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.0</span></pre></div>
<hr>
<p><strong>Levenshtein Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">LevenshteinMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>sitting<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>kitten<span class="pl-pds">"</span></span>) <span class="pl-c">// 3</span>
<span class="pl-en">LevenshteinMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>cake<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>drake<span class="pl-pds">"</span></span>) <span class="pl-c">// 2</span></pre></div>
<p><sup>Note the exception of integers, rather than doubles, being returned.</sup></p>
<hr>
<p><strong>N-Gram Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">NGramMetric</span>(<span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>night<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>nacht<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.6</span>
<span class="pl-en">NGramMetric</span>(<span class="pl-c1">2</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>night<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>nacht<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.25</span>
<span class="pl-en">NGramMetric</span>(<span class="pl-c1">2</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>context<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>contact<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.5</span></pre></div>
<p><sup>Note you must specify the size of the n-gram you wish to use.</sup></p>
<hr>
<p><strong>Overlap Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">OverlapMetric</span>(<span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>night<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>nacht<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.6</span>
<span class="pl-en">OverlapMetric</span>(<span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>context<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>contact<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.7142857142857143</span></pre></div>
<p><sup>Note you must specify the size of the n-gram you wish to use.</sup></p>
<hr>
<p><strong>Ratcliff/Obershelp Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">RatcliffObershelpMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>aleksander<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>alexandre<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.7368421052631579</span>
<span class="pl-en">RatcliffObershelpMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>pennsylvania<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>pencilvaneya<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.6666666666666666</span></pre></div>
<hr>
<p><strong>Weighted Levenshtein Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">WeightedLevenshteinMetric</span>(<span class="pl-c1">10</span>, <span class="pl-c1">0.1</span>, <span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>book<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>back<span class="pl-pds">"</span></span>) <span class="pl-c">// 2</span>
<span class="pl-en">WeightedLevenshteinMetric</span>(<span class="pl-c1">10</span>, <span class="pl-c1">0.1</span>, <span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>hosp<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>hospital<span class="pl-pds">"</span></span>) <span class="pl-c">// 0.4</span>
<span class="pl-en">WeightedLevenshteinMetric</span>(<span class="pl-c1">10</span>, <span class="pl-c1">0.1</span>, <span class="pl-c1">1</span>).compare(<span class="pl-s"><span class="pl-pds">"</span>hospital<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>hosp<span class="pl-pds">"</span></span>) <span class="pl-c">// 40</span></pre></div>
<p><sup>Note you must specify the weight of each operation. Delete, insert, and then substitute. Note that while a double is returned, it can be outside the range of 0 to 1, based upon the weights used.</sup></p>
<hr>
<h2>
<a id="phonetic-package" class="anchor" href="#phonetic-package" aria-hidden="true"><span class="octicon octicon-link"></span></a>Phonetic package</h2>
<p>Useful for indexing by word pronunciation and performing sounds-like comparisons. All metrics return a boolean value indicating if the two strings sound the same, per the algorithm used. All metrics have an algorithm counterpart which provide the means to perform indexing by word pronunciation.</p>
<hr>
<p><strong>Metaphone Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">MetaphoneMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>merci<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>mercy<span class="pl-pds">"</span></span>) <span class="pl-c">// true</span>
<span class="pl-en">MetaphoneMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>dumb<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>gum<span class="pl-pds">"</span></span>) <span class="pl-c">// false</span></pre></div>
<hr>
<p><strong>Metaphone Algorithm:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">MetaphoneAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>dumb<span class="pl-pds">"</span></span>) <span class="pl-c">// tm</span>
<span class="pl-en">MetaphoneAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>knuth<span class="pl-pds">"</span></span>) <span class="pl-c">// n0</span></pre></div>
<hr>
<p><strong>NYSIIS Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">NysiisMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>ham<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>hum<span class="pl-pds">"</span></span>) <span class="pl-c">// true</span>
<span class="pl-en">NysiisMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>dumb<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>gum<span class="pl-pds">"</span></span>) <span class="pl-c">// false</span></pre></div>
<hr>
<p><strong>NYSIIS Algorithm:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">NysiisAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>macintosh<span class="pl-pds">"</span></span>) <span class="pl-c">// mcant</span>
<span class="pl-en">NysiisAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>knuth<span class="pl-pds">"</span></span>) <span class="pl-c">// nnat</span></pre></div>
<hr>
<p><strong>Refined NYSIIS Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">RefinedNysiisMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>ham<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>hum<span class="pl-pds">"</span></span>) <span class="pl-c">// true</span>
<span class="pl-en">RefinedNysiisMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>dumb<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>gum<span class="pl-pds">"</span></span>) <span class="pl-c">// false</span></pre></div>
<hr>
<p><strong>Refined NYSIIS Algorithm:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">RefinedNysiisAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>macintosh<span class="pl-pds">"</span></span>) <span class="pl-c">// mcantas</span>
<span class="pl-en">RefinedNysiisAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>westerlund<span class="pl-pds">"</span></span>) <span class="pl-c">// wastarlad</span></pre></div>
<hr>
<p><strong>Refined Soundex Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">RefinedSoundexMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>robert<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>rupert<span class="pl-pds">"</span></span>) <span class="pl-c">// true</span>
<span class="pl-en">RefinedSoundexMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>robert<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>rubin<span class="pl-pds">"</span></span>) <span class="pl-c">// false</span></pre></div>
<hr>
<p><strong>Refined Soundex Algorithm:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">RefinedSoundexAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>hairs<span class="pl-pds">"</span></span>) <span class="pl-c">// h093</span>
<span class="pl-en">RefinedSoundexAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>lambert<span class="pl-pds">"</span></span>) <span class="pl-c">// l7081096</span></pre></div>
<hr>
<p><strong>Soundex Metric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">SoundexMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>robert<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>rupert<span class="pl-pds">"</span></span>) <span class="pl-c">// true</span>
<span class="pl-en">SoundexMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>robert<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>rubin<span class="pl-pds">"</span></span>) <span class="pl-c">// false</span></pre></div>
<hr>
<p><strong>Soundex Algorithm:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">SoundexAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>rupert<span class="pl-pds">"</span></span>) <span class="pl-c">// r163</span>
<span class="pl-en">SoundexAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>lukasiewicz<span class="pl-pds">"</span></span>) <span class="pl-c">// l222</span></pre></div>
<hr>
<h2>
<a id="convenience-objects" class="anchor" href="#convenience-objects" aria-hidden="true"><span class="octicon octicon-link"></span></a>Convenience objects</h2>
<p><strong>StringAlgorithm:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">StringAlgorithm</span>.computeWithMetaphone(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)
<span class="pl-en">StringAlgorithm</span>.computeWithNysiis(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<p><strong>StringMetric:</strong></p>
<div class="highlight highlight-scala"><pre><span class="pl-en">StringMetric</span>.compareWithJaccard(<span class="pl-c1">1</span>)(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>abcxyz<span class="pl-pds">"</span></span>)
<span class="pl-en">StringMetric</span>.compareWithJaroWinkler(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>abcxyz<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<h2>
<a id="decorating" class="anchor" href="#decorating" aria-hidden="true"><span class="octicon octicon-link"></span></a>Decorating</h2>
<p>It is possible to decorate algorithms and metrics with additional functionality, which you can mix and match. Decorations include:</p>
<ul>
<li><p><strong><a href="https://en.wikipedia.org/wiki/Memoization">withMemoization</a>:</strong> Computations and comparisons are cached. Future calls made with identical arguments will be looked up, rather than computed.</p></li>
<li><p><strong>withTransform:</strong> Transform arguments prior to computation/comparison. A handful of pre-built transforms are located in the <a href="https://github.com/rockymadden/stringmetric/blob/master/core/src/main/scala/com/rockymadden/stringmetric/transform.scala">transform module</a>.</p></li>
</ul>
<hr>
<p>Non-decorated:</p>
<div class="highlight highlight-scala"><pre><span class="pl-en">MetaphoneAlgorithm</span>.compute(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)
<span class="pl-en">MetaphoneMetric</span>.compare(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>abcxyz<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<p>Using memoization:</p>
<div class="highlight highlight-scala"><pre>(<span class="pl-en">MetaphoneAlgorithm</span> withMemoization).compute(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<p>Using a transform so that we only examine alphabetical characters:</p>
<div class="highlight highlight-scala"><pre>(<span class="pl-en">MetaphoneAlgorithm</span> withTransform filterAlpha).compute(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)
(<span class="pl-en">MetaphoneMetric</span> withTransform filterAlpha).compare(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>abcxyz<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<p>Using a functionally composed transform so that we only examine alphabetical characters, but the case will not matter:</p>
<div class="highlight highlight-scala"><pre><span class="pl-k">val</span> <span class="pl-en">composedTransform</span> <span class="pl-k">=</span> (filterAlpha andThen ignoreAlphaCase)
(<span class="pl-en">MetaphoneAlgorithm</span> withTransform composedTransform).compute(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)
(<span class="pl-en">MetaphoneMetric</span> withTransform composedTransform).compare(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>abcxyz<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<p>Making your own transform:</p>
<div class="highlight highlight-scala"><pre><span class="pl-k">val</span> <span class="pl-en">myTransform</span><span class="pl-k">:</span> <span class="pl-en">StringTransform</span> <span class="pl-k">=</span> (ca) <span class="pl-k">=></span> ca.filter(_ <span class="pl-k">==</span> <span class="pl-c1">'x'</span>)
(<span class="pl-en">MetaphoneAlgorithm</span> withTransform myTransform).compute(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)
(<span class="pl-en">MetaphoneMetric</span> withTransform myTransform).compare(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>, <span class="pl-s"><span class="pl-pds">"</span>abcxyz<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<p>Using memoization and a transform:</p>
<div class="highlight highlight-scala"><pre>((<span class="pl-en">MetaphoneAlgorithm</span> withMemoization) withTransform filterAlpha).compute(<span class="pl-s"><span class="pl-pds">"</span>abcdef<span class="pl-pds">"</span></span>)</pre></div>
<hr>
<h2>
<a id="building-the-clis" class="anchor" href="#building-the-clis" aria-hidden="true"><span class="octicon octicon-link"></span></a>Building the CLIs</h2>
<div class="highlight highlight-shell"><pre>$ git clone https://github.com/rockymadden/stringmetric.git
$ <span class="pl-c1">cd</span> stringmetric
$ sbt clean package
$ ./project/build.sh
$ ./target/cli/jarometric abc xyz</pre></div>
<hr>
<h2>
<a id="using-the-clis" class="anchor" href="#using-the-clis" aria-hidden="true"><span class="octicon octicon-link"></span></a>Using the CLIs</h2>
<p>Get help:</p>
<div class="highlight highlight-shell"><pre>$ metaphonemetric --help
Compares two strings to determine <span class="pl-k">if</span> they are phonetically similarly, per the Metaphone algorithm.
Syntax:
metaphonemetric [Options] string1 string2...
Options:
-h, --help
Outputs description, syntax, and options.</pre></div>
<hr>
<p>Get comparison value with metrics:</p>
<div class="highlight highlight-shell"><pre>$ jarowinklermetric dog dawg
0.75</pre></div>
<hr>
<p>Get representation value with phonetic algorithms:</p>
<div class="highlight highlight-shell"><pre>$ metaphonealgorithm dog
tk</pre></div>
<hr>
<h2>
<a id="license" class="anchor" href="#license" aria-hidden="true"><span class="octicon octicon-link"></span></a>License</h2>
<pre><code>The MIT License (MIT)
Copyright (c) 2013 Rocky Madden (http://rockymadden.com/)
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
</code></pre>
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