title: When are n-grams (n>3) important as opposed to just bigrams or trigrams?
body: <p>I am just wondering what is the use of n-grams (n>3) (and their occurrence frequency) considering the computational overhead in computing them. Are there any applications where bigrams or trigrams are simply not enough? </p>
  
  <p>If so, what is the state-of-the-art in n-gram extraction? Any suggestions? I am aware of the following:</p>
  
  <ul>
  <li><a href="http://acl.ldc.upenn.edu/C/C94/C94-1101.pdf">A new method of n-gram statistics for large number of n and automatic
  extraction of words and phrases from large text data of Japanese</a></li>
  <li><a href="http://acl.ldc.upenn.edu/J/J01/J01-1001.pdf">Using suffix arrays to compute term frequency and document frequency
  for all substrings in a corpus</a> </li>
  <li><a href="http://acl.ldc.upenn.edu/J/J90/J90-1003.pdf">Word association norms, mutual information, and lexicography</a></li>
  <li><a href="http://acl.ldc.upenn.edu/J/J93/J93-1007.pdf">Retrieving collocations from text: Xtract</a></li>
  </ul>