Title
Amortized analyses of self-organizing sequential search heuristics
Abstract
The performance of sequential search can be enhanced by the use of heuristics that move elements closer to the front of the list as they are found. Previous analyses have characterized the performance of such heuristics probabilistically. In this article, we use amortization to analyze the heuristics in a worst-case sense; the relative merit of the heuristics in this analysis is different in the probabilistic analyses. Experiments show that the behavior of the heuristics on real data is more closely described by the amortized analyses than by the probabilistic analyses.
Year
DOI
Venue
1985
10.1145/3341.3349
Commun. ACM
Keywords
Field
DocType
probabilistic analysis,sequential search heuristics,previous analysis,amortized analysis,move element,sequential search,relative merit,heuristics probabilistically,worst-case sense,self organization
Data structure,Computer science,Amortization (business),Amortization,Theoretical computer science,Heuristics,Artificial intelligence,Probabilistic logic,Linear search
Journal
Volume
Issue
ISSN
28
4
0001-0782
Citations 
PageRank 
References 
77
38.41
8
Authors
2
Name
Order
Citations
PageRank
Jon L. Bentley138066.40
Catherine C. McGeoch226259.29