<p>Seems like a promising algorithm to measure similarity of a list is to use Spearman footrule distance <a href="http://people.revoledu.com/kardi/tutorial/Similarity/FootruleDistance.html" rel="nofollow">http://people.revoledu.com/kardi/tutorial/Similarity/FootruleDistance.html</a>, or more involved and taking order into account, discounted cumulative gain, DCG, <a href="https://www.kaggle.com/wiki/NormalizedDiscountedCumulativeGain" rel="nofollow">https://www.kaggle.com/wiki/NormalizedDiscountedCumulativeGain</a> .</p>

<p>A very good resource to that topic is</p>

<p><a href="http://arxiv.org/pdf/1107.2691.pdf" rel="nofollow">http://arxiv.org/pdf/1107.2691.pdf</a></p>

<p>and</p>

<p><a href="http://theory.stanford.edu/~sergei/slides/www10-metrics.pdf" rel="nofollow">http://theory.stanford.edu/~sergei/slides/www10-metrics.pdf</a></p>
Compare two ordered lists for similarity
<p>Assume I have two lists:</p>

<pre><code>L1: [1,2,3,4]
L2: [1,3,2,4,5]
</code></pre>

<p>How can I compute the similarity between theses two lists?</p>

<p>If these two lists would be of same length, Spearman and Kendall seem to be the answer, but can this principle also extended to lists of diverging length?</p>