License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CPM.2021.18
URN: urn:nbn:de:0030-drops-139699
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/13969/
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Kim, Sung-Hwan ; Cho, Hwan-Gue

A Compact Index for Cartesian Tree Matching

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LIPIcs-CPM-2021-18.pdf (2 MB)

Abstract

Cartesian tree matching is a recently introduced string matching problem in which two strings match if their corresponding Cartesian trees are the same. It is considered appropriate to find patterns regarding their shapes especially in numerical time series data. While many related problems have been addressed, developing a compact index has received relatively less attention. In this paper, we present a 3n+o(n)-bit index that can count the number of occurrences of a Cartesian tree pattern in ?(m) time where n and m are the text and pattern length. To the best of our knowledge, this work is the first ?(n)-bit compact data structure for indexing for this problem.

BibTeX - Entry

@InProceedings{kim_et_al:LIPIcs.CPM.2021.18,
  author =	{Kim, Sung-Hwan and Cho, Hwan-Gue},
  title =	{{A Compact Index for Cartesian Tree Matching}},
  booktitle =	{32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)},
  pages =	{18:1--18:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-186-3},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{191},
  editor =	{Gawrychowski, Pawe{\l} and Starikovskaya, Tatiana},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/13969},
  URN =		{urn:nbn:de:0030-drops-139699},
  doi =		{10.4230/LIPIcs.CPM.2021.18},
  annote =	{Keywords: String Matching, Suffix Array, FM-index, Compact Index, Cartesian Tree Matching}
}

Keywords: String Matching, Suffix Array, FM-index, Compact Index, Cartesian Tree Matching
Collection: 32nd Annual Symposium on Combinatorial Pattern Matching (CPM 2021)
Issue Date: 2021
Date of publication: 30.06.2021

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