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Length-$q$ substrings, or $q$-grams, can represent important characteristicsof text data, and determining the frequencies of all $q$-grams contained in thedata is an important problem with many applications in the field of data miningand machine learning. In this paper, we consider the problem of calculating the{\em non-overlapping frequencies} of all $q$-grams in a text given incompressed form, namely, as a straight line program (SLP). We show that theproblem can be solved in $O(q^2n)$ time and $O(qn)$ space where $n$ is the sizeof the SLP. This generalizes and greatly improves previous work (Inenaga &Bannai, 2009) which solved the problem only for $q=2$ in $O(n^4\log n)$ timeand $O(n^3)$ space.

Computing q-gram Non-overlapping Frequencies on SLP Compressed Texts