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        <identifier>oai:drops-oai.dagstuhl.de:7325</identifier>
        <datestamp>2024-03-06T09:40:07Z</datestamp>
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          <dc:title>Time-Space Trade-Offs for Lempel-Ziv Compressed Indexing</dc:title>
          <dc:creator>Bille, Philip</dc:creator>
          <dc:creator>Ettienne, Mikko Berggren</dc:creator>
          <dc:creator>Gørtz, Inge Li</dc:creator>
          <dc:creator>Vildhøj, Hjalte Wedel</dc:creator>
          <dc:subject>compressed indexing</dc:subject>
          <dc:subject>pattern matching</dc:subject>
          <dc:subject>LZ77</dc:subject>
          <dc:subject>prefix search</dc:subject>
          <dc:description>Given a string S, the compressed indexing problem is to preprocess S into a compressed representation that supports fast substring queries. The goal is to use little space relative to the compressed size of S while supporting fast queries. We present a compressed index based on the Lempel-Ziv 1977 compression scheme. Let n, and z denote the size of the input string, and the compressed LZ77 string, respectively. We obtain the following time-space trade-offs. Given a pattern string P of length m, we can solve the problem in&#13;
&#13;
(i) O(m + occ lglg n) time using O(z lg(n/z) lglg z) space, or&#13;
(ii) O(m(1 + lg^e z / lg(n/z)) + occ(lglg n + lg^e z)) time using O(z lg(n/z)) space, for any 0 &lt; e &lt; 1&#13;
&#13;
In particular, (i) improves the leading term in the query time of the previous best solution from O(m lg m) to O(m) at the cost of increasing the space by a factor lglg z. Alternatively, (ii) matches the previous best space bound, but has a leading term in the query time of O(m(1+lg^e z / lg(n/z))). However, for any polynomial compression ratio, i.e., z = O(n^{1-d}), for constant d &gt; 0, this becomes O(m). Our index also supports extraction of any substring of length l in O(l + lg(n/z)) time. Technically, our results are obtained by novel extensions and combinations of existing data structures of independent interest, including a new batched variant of weak prefix search.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Philip Bille and Mikko Berggren Ettienne and Inge Li Gørtz and Hjalte Wedel Vildhøj</dc:contributor>
          <dc:date>2017</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 78, 28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.CPM.2017.16</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-73254</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2017.16</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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