title: Similarity between two data sets or arrays
body: <p>Let's say I have a dataset that look like this: </p>
  
  <pre><code>{A:1, B:3, C:6, D:6}
  </code></pre>
  
  <p>I also have a list of other sets to compare my specific set:  </p>
  
  <pre><code>{A:1, B:3, C:6, D:6},  
  {A:2, B:3, C:6, D:6},  
  {A:99, B:3, C:6, D:6},  
  {A:5, B:1, C:6, D:9},  
  {A:4, B:2, C:2, D:6}
  </code></pre>
  
  <p>My entries could be visualized as a Table (with four columns, A, B, C, D, and E).</p>
  
  <p>How can I find the set with the most similarity?
  For this example, row 1 is a perfect match and row 2 is a close second, while row 3 is quite far away.</p>
  
  <p>I am thinking of calculating a simple delta, for example: <code>Abs(a1 - a2) +  Abs(b1 - b2) + etc</code> and perhaps get a <a href="http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient#Mathematical_properties" rel="nofollow noreferrer">correlation value</a> for the entries with the best deltas.</p>
  
  <p>Is this a valid way?
  And what is the name of this problem? </p>