Speeding Up q-Gram Mining on Grammar-Based Compressed Texts

摘要

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 T 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 g-gram frequencies problem on a trie-like structure of size m = |T| - dup(q,T), where dup(q,T) 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 O(min |T| - dup(q,T),qn}), improving our previous O(qn) algorithm when q = Ω{|T|).