Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 45 tok/s
Gemini 2.5 Pro 54 tok/s Pro
GPT-5 Medium 22 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 99 tok/s Pro
Kimi K2 183 tok/s Pro
GPT OSS 120B 467 tok/s Pro
Claude Sonnet 4 38 tok/s Pro
2000 character limit reached

Dynamic index, LZ factorization, and LCE queries in compressed space (1504.06954v4)

Published 27 Apr 2015 in cs.DS

Abstract: In this paper, we present the following results: (1) We propose a new \emph{dynamic compressed index} of $O(w)$ space, that supports searching for a pattern $P$ in the current text in $O(|P| f(M,w) + \log w \log |P| \log* M (\log N + \log |P| \log* M) + \mathit{occ} \log N)$ time and insertion/deletion of a substring of length $y$ in $O((y+ \log N\log* M)\log w \log N \log* M)$ time, where $N$ is the length of the current text, $M$ is the maximum length of the dynamic text, $z$ is the size of the Lempel-Ziv77 (LZ77) factorization of the current text, $f(a,b) = O(\min { \frac{\log\log a \log\log b}{\log\log\log a}, \sqrt{\frac{\log b}{\log\log b}} })$ and $w = O(z \log N \log*M)$. (2) We propose a new space-efficient LZ77 factorization algorithm for a given text of length $N$, which runs in $O(N f(N,w') + z \log w' \log3 N (\log* N)2)$ time with $O(w')$ working space, where $w' =O(z \log N \log* N)$. (3) We propose a data structure of $O(w)$ space which supports longest common extension (LCE) queries on the text in $O(\log N + \log \ell \log* N)$ time, where $\ell$ is the output LCE length. On top of the above contributions, we show several applications of our data structures which improve previous best known results on grammar-compressed string processing.

Citations (22)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube