Evidence map›Paper›PMID 33265675›Full record

ArticleEntropy (Basel, Switzerland)2018

Marking Vertices to Find Graph Isomorphism Mapping Based on Continuous-Time Quantum Walk.

Xin Wang, Yi Zhang, Kai Lu, Xiaoping Wang, Kai Liu

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xin WangCollege of Computer Science, National University of Defense Technology, Changsha 410073, China.
Yi ZhangCollege of Computer Science, National University of Defense Technology, Changsha 410073, China.
Kai LuCollege of Computer Science, National University of Defense Technology, Changsha 410073, China.
Xiaoping WangCollege of Computer Science, National University of Defense Technology, Changsha 410073, China.
Kai LiuCollege of Computer Science, National University of Defense Technology, Changsha 410073, China.

Funding

National Science Foundation (NSF) China 61402492, 61402486, 61379146the HUNAN Province Science Foundation 2017RS3045the laboratory pre-research fund 9140C810106150C81001The National Key Research and Development Program of China 2016YFB0200401
6 · The paper itself

Abstract

The isomorphism problem involves judging whether two graphs are topologically the same and producing structure-preserving isomorphism mapping. It is widely used in various areas. Diverse algorithms have been proposed to solve this problem in polynomial time, with the help of quantum walks. Some of these algorithms, however, fail to find the isomorphism mapping. Moreover, most algorithms have very limited performance on regular graphs which are generally difficult to deal with due to their symmetry. We propose IsoMarking to discover an isomorphism mapping effectively, based on the quantum walk which is sensitive to topological structures. Firstly, IsoMarking marks vertices so that it can reduce the harmful influence of symmetry. Secondly, IsoMarking can ascertain whether the current candidate bijection is consistent with existing bijections and eventually obtains qualified mapping. Thirdly, our experiments on 1585 pairs of graphs demonstrate that our algorithm performs significantly better on both ordinary graphs and regular graphs.

Indexed as

continuous-time quantum walkdata mininggraph isomorphismgraph miningisomorphism mapping

Identifiers

PMID33265675
PMCPMC7513114

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.