Speeding up q-gram mining on grammar-based compressed texts

Abstract

We present an efficient algorithm for calculating q-gram frequencies on strings represented in compressed form, namely, as a straight line program (SLP). Given an SLP of size n that represents string T, the algorithm computes the occurrence frequencies of all q-grams in T, by reducing the problem to the weighted q-gram frequencies problem on a trie-like structure of size , where is a quantity that represents the amount of redundancy that the SLP captures with respect to q-grams. The reduced problem can be solved in linear time. Since m = O(qn), the running time of our algorithm is , improving our previous O(qn) algorithm when q = Ω(|T|/n). © 2012 Springer-Verlag.