Faster subsequence recognition in compressed strings

Abstract. Processing compressed strings without decompression is often essential when dealing with massive data sets. We consider local subsequence recognition problems on strings compressed by straight-line programs (SLP), which is closely related to Lempel–Ziv compression. For an SLP-compressed text of length m, and an uncompressed pattern of length n, C´egielski et al. [4] gave an algorithm for local subsequence recognition running in time O(mn2 log n). We improve the running time

• Type: Journal
• Year: 2007
• Where: CORR
• Authors: Alexandre Tiskin
• Keywords: CORR 2007, Education, Local Subsequence Recognition, Massive Data Sets, Subsequence Recognition Problems