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? 

If so, what is the state-of-the-art in n-gram extraction? Any suggestions? I am aware of the following:

* [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](http://acl.ldc.upenn.edu/C/C94/C94-1101.pdf)
* [Using suffix arrays to compute term frequency and document frequency
for all substrings in a corpus](http://acl.ldc.upenn.edu/J/J01/J01-1001.pdf)
* [Word association norms, mutual information, and lexicography](http://acl.ldc.upenn.edu/J/J90/J90-1003.pdf)
* [Retrieving collocations from text: Xtract](http://acl.ldc.upenn.edu/J/J93/J93-1007.pdf)