A space efficient method for the lowest common ancestor problem and an application to finding negative cycles

1977 ◽  
Author(s):  
David Maier
Keyword(s):  
Efficient Method ◽  
Common Ancestor ◽  
Lowest Common Ancestor ◽  
Negative Cycles

scholarly journals On the Distribution of Depths in Increasing Trees

10.37236/409 ◽  
2010 ◽  
Vol 17 (1) ◽  
Author(s):  
Markus Kuba ◽  
Stephan Wagner
Keyword(s):  
Common Ancestor ◽  
Short Note ◽  
Bijective Proof ◽  
Lowest Common Ancestor ◽  
Recursive Trees

By a theorem of Dobrow and Smythe, the depth of the $k$th node in very simple families of increasing trees (which includes, among others, binary increasing trees, recursive trees and plane ordered recursive trees) follows the same distribution as the number of edges of the form $j-(j+1)$ with $j < k$. In this short note, we present a simple bijective proof of this fact, which also shows that the result actually holds within a wider class of increasing trees. We also discuss some related results that follow from the bijection as well as a possible generalization. Finally, we use another similar bijection to determine the distribution of the depth of the lowest common ancestor of two nodes.

PARALLEL RANGE MINIMA ON COARSE GRAINED MULTICOMPUTERS

1999 ◽  
Vol 10 (04) ◽  
pp. 375-389
Author(s):  
H. MONGELLI ◽  
S. W. SONG
Keyword(s):  
Common Ancestor ◽  
Basic Problem ◽  
Coarse Grained ◽  
Time Range ◽  
Communication Overhead ◽  
Constant Number ◽  
Real Numbers ◽  
Graph Problems ◽  
Large N ◽  
Lowest Common Ancestor

Given an array of n real numbers A=(a0, a1, …, an-1), define MIN(i,j)= min {ai,…,aj}. The range minima problem consists of preprocessing array A such that queries MIN(i,j), for any 0≤i≤n-1 can be answered in constant time. Range minima is a basic problem that appears in many other important graph problems such as lowest common ancestor, Euler tour, etc. In this work we present a parallel algorithm under the CGM model (coarse grained multicomputer), that solves the range minima problem in O(n/p) time and constant number of communication rounds. The communication overhead involves the transmission of p numbers (independent of n). We show promising experimental results with speedup curves approximating the optimal for large n.

scholarly journals A scalable approach to computing representative lowest common ancestor in directed acyclic graphs

2013 ◽  
Vol 513 ◽  
pp. 25-37 ◽  
Author(s):  
Santanu Kumar Dash ◽  
Sven-Bodo Scholz ◽  
Stephan Herhut ◽  
Bruce Christianson
Keyword(s):  
Common Ancestor ◽  
Directed Acyclic Graphs ◽  
Acyclic Graphs ◽  
Lowest Common Ancestor

The lowest common ancestor problem on a tree with an unfixed root

1999 ◽  
Vol 119 (1-2) ◽  
pp. 125-130 ◽  
Author(s):  
Biing-Feng Wang ◽  
Jiunn-Nan Tsai ◽  
Yuan-Cheng Chuang
Keyword(s):  
Common Ancestor ◽  
Lowest Common Ancestor

scholarly journals Pangolin homology associated with 2019-nCoV

2020 ◽  
Author(s):  
Tao Zhang ◽  
Qunfu Wu ◽  
Zhigang Zhang
Keyword(s):  
Amino Acid ◽  
Intermediate Host ◽  
Common Ancestor ◽  
Whole Genome ◽  
Amino Acid Residues ◽  
Pathogenic Potential ◽  
Lowest Common Ancestor ◽  
Amino Acid Mutations ◽  
Genome Level ◽  
Novel Coronavirus

AbstractTo explore potential intermediate host of a novel coronavirus is vital to rapidly control continuous COVID-19 spread. We found genomic and evolutionary evidences of the occurrence of 2019-nCoV-like coronavirus (named as Pangolin-CoV) from dead Malayan Pangolins. Pangolin-CoV is 91.02% and 90.55% identical at the whole genome level to 2019-nCoV and BatCoV RaTG13, respectively. Pangolin-CoV is the lowest common ancestor of 2019-nCoV and RaTG13. The S1 protein of Pangolin-CoV is much more closely related to 2019-nCoV than RaTG13. Five key amino-acid residues involved in the interaction with human ACE2 are completely consistent between Pangolin-CoV and 2019-nCoV but four amino-acid mutations occur in RaTG13. It indicates Pangolin-CoV has similar pathogenic potential to 2019-nCoV, and would be helpful to trace the origin and probable intermediate host of 2019-nCoV.

Fast Smallest Lowest Common Ancestor Computation Based on Stable Match

2013 ◽  
Vol 28 (2) ◽  
pp. 366-381
Author(s):  
Jun-Feng Zhou ◽  
Guo-Xiang Lan ◽  
Zi-Yang Chen ◽  
Xian Tang
Keyword(s):  
Common Ancestor ◽  
Stable Match ◽  
Lowest Common Ancestor

Research and Implementation of XML Keyword Search Algorithm Based on Semantic Relatives

2011 ◽  
Vol 267 ◽  
pp. 811-815
Author(s):  
Ming Yan Shen ◽  
Xin Li ◽  
Xiang Fu Meng
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Search Algorithm ◽  
Search Method ◽  
Document Structure ◽  
Xml Documents ◽  
Xml Keyword Search ◽  
Lowest Common Ancestor ◽  
Xml Document

The XML keyword search has been used widely in the application of XML documents. Most of the XML keyword search approaches are based on the LCA (lowest common ancestor) or its variants, which usually leads to the un-ideal recall and precision. This paper presents a novel XML keyword search method which based on semantic relatives. The method fully considers the semantic characteristics of the XML document structure. Based on the stack, the algorithm is also presented to merge the semantic relative nodes containing the keyword as the results of XML keyword search. The results of experiments have been identified the efficient and efficiency of our method.

scholarly journals XKFitler

2011 ◽  
Vol 1 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Weidong Yang ◽  
Fei Fang ◽  
Nan Li ◽  
Zhongyu (Joan) Lu
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Stream Processing ◽  
Query Languages ◽  
Information Discovery ◽  
Text Documents ◽  
Filter System ◽  
Lowest Common Ancestor ◽  
Xml Stream ◽  
User Friendly

Most existing XML stream processing systems adopt full structured query languages, such as XPath or XQuery, but they are difficult for ordinary users to learn and use. Keyword search is a user-friendly information discovery technique that has been extensively studied for text documents. This paper presents an XML stream filter system called XKFitler, which is the first system for supporting keyword search over XML stream. In XKFitler, the concepts of XLCA (eXclusive Lowest Common Ancestor) and XLCA Connecting Tree (XLCACT) are used to define the search semantic and results of keywords, and present an approach to filter XML stream according to keywords. The prototype XKFilter is implemented in the experiments.

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