Faster subsequence recognition in compressed strings

Details Faster subsequence recognition in compressed strings Faster subsequence recognition in compressed strings

2007-07-23

arxiv.org/abs/0707.3407v4

Computer Science

Data Structures and Algorithms

Scientific paper

Computation on compressed strings is one of the key approaches to processing 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 $\bar m$, and an uncompressed pattern of length $n$, C{\'e}gielski et al. gave an algorithm for local subsequence recognition running in time $O(\bar mn^2 \log n)$. We improve the running time to $O(\bar mn^{1.5})$. Our algorithm can also be used to compute the longest common subsequence between a compressed text and an uncompressed pattern in time $O(\bar mn^{1.5})$; the same problem with a compressed pattern is known to be NP-hard.

Affiliated with

Also associated with

No associations

Rating

Faster subsequence recognition in compressed strings does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Faster subsequence recognition in compressed strings, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Faster subsequence recognition in compressed strings will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-109914