Optimal skeleton Huffman trees

Shmuel T. Klein; Tamar C. Serebro; Dana Shapira

doi:10.1007/978-3-319-67428-5_21

Optimal skeleton Huffman trees

Shmuel T. Klein, Tamar C. Serebro, Dana Shapira

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

A skeleton Huffman tree is a Huffman tree from which all complete subtrees of depth h≥1 have been pruned. Skeleton Huffman trees are used to save storage and enhance processing time in several applications such as decoding, compressed pattern matching and Wavelet trees for random access. However, the straightforward way of basing the construction of a skeleton tree on a canonical Huffman tree does not necessarily yield the least number of nodes. The notion of optimal skeleton trees is introduced, and an algorithm for achieving such trees is investigated. The resulting more compact trees can be used to further enhance the time and space complexities of the corresponding algorithms.

Original language	English
Title of host publication	String Processing and Information Retrieval - 24th International Symposium, SPIRE 2017, Proceedings
Editors	Rossano Venturini, Gabriele Fici, Marinella Sciortino
Pages	241-253
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-319-67428-5_21
State	Published - 2017
Event	24th International Symposium on String Processing and Information Retrieval, SPIRE 2017 - Palermo, Italy Duration: 26 Sep 2017 → 29 Sep 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10508 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	24th International Symposium on String Processing and Information Retrieval, SPIRE 2017
Country/Territory	Italy
City	Palermo
Period	26/09/17 → 29/09/17

Access to Document

10.1007/978-3-319-67428-5_21

Cite this

Klein, S. T., Serebro, T. C., & Shapira, D. (2017). Optimal skeleton Huffman trees. In R. Venturini, G. Fici, & M. Sciortino (Eds.), String Processing and Information Retrieval - 24th International Symposium, SPIRE 2017, Proceedings (pp. 241-253). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10508 LNCS). https://doi.org/10.1007/978-3-319-67428-5_21

Klein, Shmuel T. ; Serebro, Tamar C. ; Shapira, Dana. / Optimal skeleton Huffman trees. String Processing and Information Retrieval - 24th International Symposium, SPIRE 2017, Proceedings. editor / Rossano Venturini ; Gabriele Fici ; Marinella Sciortino. 2017. pp. 241-253 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Optimal skeleton Huffman trees",

abstract = "A skeleton Huffman tree is a Huffman tree from which all complete subtrees of depth h≥1 have been pruned. Skeleton Huffman trees are used to save storage and enhance processing time in several applications such as decoding, compressed pattern matching and Wavelet trees for random access. However, the straightforward way of basing the construction of a skeleton tree on a canonical Huffman tree does not necessarily yield the least number of nodes. The notion of optimal skeleton trees is introduced, and an algorithm for achieving such trees is investigated. The resulting more compact trees can be used to further enhance the time and space complexities of the corresponding algorithms.",

author = "Klein, {Shmuel T.} and Serebro, {Tamar C.} and Dana Shapira",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 24th International Symposium on String Processing and Information Retrieval, SPIRE 2017 ; Conference date: 26-09-2017 Through 29-09-2017",

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doi = "10.1007/978-3-319-67428-5_21",

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Klein, ST, Serebro, TC & Shapira, D 2017, Optimal skeleton Huffman trees. in R Venturini, G Fici & M Sciortino (eds), String Processing and Information Retrieval - 24th International Symposium, SPIRE 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10508 LNCS, pp. 241-253, 24th International Symposium on String Processing and Information Retrieval, SPIRE 2017, Palermo, Italy, 26/09/17. https://doi.org/10.1007/978-3-319-67428-5_21

Optimal skeleton Huffman trees. / Klein, Shmuel T.; Serebro, Tamar C.; Shapira, Dana.
String Processing and Information Retrieval - 24th International Symposium, SPIRE 2017, Proceedings. ed. / Rossano Venturini; Gabriele Fici; Marinella Sciortino. 2017. p. 241-253 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10508 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - A skeleton Huffman tree is a Huffman tree from which all complete subtrees of depth h≥1 have been pruned. Skeleton Huffman trees are used to save storage and enhance processing time in several applications such as decoding, compressed pattern matching and Wavelet trees for random access. However, the straightforward way of basing the construction of a skeleton tree on a canonical Huffman tree does not necessarily yield the least number of nodes. The notion of optimal skeleton trees is introduced, and an algorithm for achieving such trees is investigated. The resulting more compact trees can be used to further enhance the time and space complexities of the corresponding algorithms.

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Klein ST, Serebro TC, Shapira D. Optimal skeleton Huffman trees. In Venturini R, Fici G, Sciortino M, editors, String Processing and Information Retrieval - 24th International Symposium, SPIRE 2017, Proceedings. 2017. p. 241-253. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-67428-5_21

Optimal skeleton Huffman trees

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