Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

H. Lynn Beus

dblp:77/3551 · DBLP profile ↗
← Back
3ranked-venue papers
2as first author
0since 2021 · last 1987
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Algorithms and data structures · 67% Information theory · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › sequence algorithms › sorting
comparison sorting
0.011970
The Use of Information in Sorting · J. ACM 1970
Information theory › information-theoretic limits
information-theoretic lower bounds
0.011970
The Use of Information in Sorting · J. ACM 1970
Algorithms and data structures › sequence algorithms
sorting
0.011970
The Use of Information in Sorting · J. ACM 1970

Methods — techniques the papers use, named apart from their topics

information theory · 0.0
YearPublicationVenuePosition
1987 An improved corner detection algorithm based on chain-coded plane curves
H. Lynn Beus, Steven S. H. Tiu
Pattern Recognit.1
1982 On-line recognition of hand-printed Korean characters
Y. H. Huh, H. Lynn Beus
Pattern Recognit.2
1970 The Use of Information in Sorting
abstract
The information-gathering aspect of sorting is considered from a theoretical viewpoint. A large class, R, of sorting algorithms is defined, based on the idea of information use. Properties of this algorithm class are developed, and it is noted that several well-known sorting algorithms are closely related to algorithms in R . The Binary Tree Sort is shown to be in R and to have unique properties in this class. A vector is defined which characterizes the information-gathering efficiency of the algorithms of R . Finally, a more general class of algorithms is defined, and some of the definitions extended to this class. Two intriguing conjectures are given which appear to require graph theory or combinatorial topology for their solution.
H. Lynn Beus
J. ACM1