2026-10-23T03:51:57Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/4240 2021-12-13T03:27:32Z 1582963302567:1597824175385 user-ucsy

A Graph Representative Structure for Detecting Automorphic Graphs Hlaing, Yu Wai Oo, Kyaw May Graphs are prevalently used to model the relationships between objects in various domains. Storing the graphs into large databases is a challengingtask as it deals with efficient space and time management. Unlike item sets inhuge transactional databases, it becomes essential to ensure the consistency ofgraph databases since relationships among edges of a graph are predominant.One of the necessary procedures required is a mechanism to check whether twographs are automorphic(duplicated) or not. Difficulty in identifying and eliminating the automorphic graphs is a challenging problem to the research community. In this paper, we propose a graph representative structure that is calledgraph code. There are three main phases: preprocessing, code generation andcode matching. In preprocessing phase, vertex list, edge list and adjacent edgeinformation are generated for input graph. In code generation, edge dictionaryplays an important role. The edge dictionary and adjacent edge information areused to generate graph codes. In code matching, the new graph code is compared with those of other graphs in graph dataset to determine whether they areautomorphic or not. The experimental results and comparisons offer a positiveresponse to the proposed structure. 2015 http://hdl.handle.net/20.500.12678/0000004240 https://meral.edu.mm/records/4240