Space-Efficient String Indexing for Wildcard Pattern Matching

Authors Moshe Lewenstein, Yakov Nekrich, Jeffrey Scott Vitter

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Moshe Lewenstein
Yakov Nekrich
Jeffrey Scott Vitter

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Moshe Lewenstein, Yakov Nekrich, and Jeffrey Scott Vitter. Space-Efficient String Indexing for Wildcard Pattern Matching. In 31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014). Leibniz International Proceedings in Informatics (LIPIcs), Volume 25, pp. 506-517, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


In this paper we describe compressed indexes that support pattern matching queries for strings with wildcards. For a constant size alphabet our data structure uses O(n.log^e(n)) bits for any e>0 and reports all occ occurrences of a wildcard string in O(m+s^g.M(n)+occ) time, where M(n)=o(log(log(log(n)))), s is the alphabet size, m is the number of alphabet symbols and g is the number of wildcard symbols in the query string. We also present an O(n)-bit index with O((m+s^g+occ).log^e(n)) query time and an O(n{log(log(n))}^2)-bit index with O((m+s^g+occ).log(log(n))) query time. These are the first non-trivial data structures for this problem that need o(n.log(n)) bits of space.
  • compressed data structures
  • compressed indexes
  • pattern matching


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