Journal ArticleDOI
On the History of the Minimum Spanning Tree Problem
Ron Graham,Pavol Hell +1 more
TLDR
There are several apparently independent sources and algorithmic solutions of the minimum spanning tree problem and their motivations, and they have appeared in Czechoslovakia, France, and Poland, going back to the beginning of this century.Abstract:
It is standard practice among authors discussing the minimum spanning tree problem to refer to the work of Kruskal(1956) and Prim (1957) as the sources of the problem and its first efficient solutions, despite the citation by both of Boruvka (1926) as a predecessor. In fact, there are several apparently independent sources and algorithmic solutions of the problem. They have appeared in Czechoslovakia, France, and Poland, going back to the beginning of this century. We shall explore and compare these works and their motivations, and relate them to the most recent advances on the minimum spanning tree problem.read more
Citations
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Journal ArticleDOI
Efficient algorithms for finding minimum spanning trees in undirected and directed graphs
TL;DR: This paper uses F-heaps to obtain fast algorithms for finding minimum spanning trees in undirected and directed graphs and can be extended to allow a degree constraint at one vertex.
Journal ArticleDOI
Deep learning networks for stock market analysis and prediction
TL;DR: A systematic analysis of the use of deep learning networks for stock market analysis and prediction using five-minute intraday data from the Korean KOSPI stock market as input data to examine the effects of three unsupervised feature extraction methods.
Journal ArticleDOI
Business process analysis in healthcare environments: A methodology based on process mining
Álvaro Rebuge,Diogo R. Ferreira +1 more
TL;DR: This work introduces a methodology for the application of process mining techniques that leads to the identification of regular behavior, process variants, and exceptional medical cases in a case study conducted at a hospital emergency service.
Journal ArticleDOI
A randomized linear-time algorithm to find minimum spanning trees
TL;DR: A randomized linear-time algorithm to find a minimum spanning tree in a connected graph with edge weights is presented, a unit-cost random-access machine with the restriction that the only operations allowed on edge weights are binary comparisons.
Journal ArticleDOI
A minimum spanning tree algorithm with inverse-Ackermann type complexity
TL;DR: A deterministic algorithm for computing a minimum spanning tree of a connected graph that uses pointers, not arrays, and it makes no numeric assumptions on the edge costs.
References
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Principles of numerical taxonomy
Robert R. Sokal,P.H.A. Sneath +1 more
TL;DR: The authors continued the story of psychology with added research and enhanced content from the most dynamic areas of the field, such as cognition, gender and diversity studies, neuroscience and more, while at the same time using the most effective teaching approaches and learning tools.