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SIAM Journal on Computing
Article . 1977 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2017
Data sources: DBLP
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Optimum Sequence Trees

Optimum sequence trees
Authors: Masahiro Miyakawa; Toshitsugu Yuba; Yoshio Sugito; Mamoru Hoshi;

Optimum Sequence Trees

Abstract

The construction problems of optimum sequence trees (or digital search trees) are considered in the following frameworks: 1. construction of optimum trees from a set of keys, 2. transformation of an arbitrary tree into an optimum one, 3. optimum insertions of keys into an optimum tree, 4. optimum deletions of keys from an optimum tree.Algorithms are shown. The number of operations needed for the algorithm in the framework 1 is at most $O(N^{2}L)$, and in the framework 2 it is at most $O(N^{3}L)$ both with $O(N)$ storage locations, where N and L are the number of keys and the length of coded keys respectively.Necessary and sufficient conditions for the optimality of sequence trees are also given.

Keywords

Analysis of algorithms and problem complexity, Algorithms in computer science, Trees

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Top 10%
Average
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