The Information-Theoretic Bound is Good for Merging
Author(s) -
Nathan Linial
Publication year - 1984
Publication title -
siam journal on computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.533
H-Index - 122
eISSN - 1095-7111
pISSN - 0097-5397
DOI - 10.1137/0213049
Subject(s) - order (exchange) , combinatorics , mathematics , linear extension , extension (predicate logic) , upper and lower bounds , constant (computer programming) , time complexity , existential quantification , discrete mathematics , binary logarithm , partially ordered set , computer science , mathematical analysis , finance , economics , programming language
Let $A = (a_1 > \cdots > a_m )$ and $B = (b_1 > \cdots > b_n )$ be given ordered lists: also let there be given some order relations between $a_i $’s and $b_j $’s. Suppose that an unknown total order exists on $A \cup B$ which is consistent with all these relations ($ = a$ linear extension of the partial order) and we wish to find out this total order by comparing pairs of elements $a_t :b_s $. If the partial order has N linear extensions, then the Information Theoretic Bound says that $\log _2 N$ steps will be required in the worst case from any such algorithm. In this paper we show that there exists an algorithm which will take no more than $C\log _2 N$ comparisons where $C = (\log _2 ((\sqrt 5 + 1)/ 2))^{ -1} $. The computation required to determine the pair $a_t :b_s $ to be compared has length polynomial in $(m + n)$. The constant C is best possible. Many related results are reviewed.
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