License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CPM.2020.4
URN: urn:nbn:de:0030-drops-121299
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12129/
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Belazzougui, Djamal ; Kucherov, Gregory

Efficient Tree-Structured Categorical Retrieval

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LIPIcs-CPM-2020-4.pdf (0.4 MB)

Abstract

We study a document retrieval problem in the new framework where D text documents are organized in a category tree with a pre-defined number h of categories. This situation occurs e.g. with taxomonic trees in biology or subject classification systems for scientific literature. Given a string pattern p and a category (level in the category tree), we wish to efficiently retrieve the t categorical units containing this pattern and belonging to the category. We propose several efficient solutions for this problem. One of them uses n(logσ(1+o(1))+log D+O(h)) + O(Δ) bits of space and O(|p|+t) query time, where n is the total length of the documents, σ the size of the alphabet used in the documents and Δ is the total number of nodes in the category tree. Another solution uses n(logσ(1+o(1))+O(log D))+O(Δ)+O(Dlog n) bits of space and O(|p|+tlog D) query time. We finally propose other solutions which are more space-efficient at the expense of a slight increase in query time.

BibTeX - Entry

@InProceedings{belazzougui_et_al:LIPIcs:2020:12129,
  author =	{Djamal Belazzougui and Gregory Kucherov},
  title =	{{Efficient Tree-Structured Categorical Retrieval}},
  booktitle =	{31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020)},
  pages =	{4:1--4:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-149-8},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{161},
  editor =	{Inge Li G{\o}rtz and Oren Weimann},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12129},
  URN =		{urn:nbn:de:0030-drops-121299},
  doi =		{10.4230/LIPIcs.CPM.2020.4},
  annote =	{Keywords: pattern matching, document retrieval, category tree, space-efficient data structures}
}

Keywords: pattern matching, document retrieval, category tree, space-efficient data structures
Collection: 31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020)
Issue Date: 2020
Date of publication: 09.06.2020

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