Emerging Trends in Computing |
Foundation of Computer Science USA |
ETC2016 - Number 2 |
March 2017 |
Authors: Maninder Rajput, Snehal Kamalapur |
13492536-0056-4564-b808-b64bf5958b9e |
Maninder Rajput, Snehal Kamalapur . Subgraph Matching Algorithm for Graph Database. Emerging Trends in Computing. ETC2016, 2 (March 2017), 15-19.
A graph is a symbolic representation of data and its relationships. It is used in many domains like bioinformatics, semantic web and chemical structures applications. Subgraph matching is a technique to retrieve set of subgraphs from dataset which are similar to query/input graph. Subgraph matching is a NP-hard. Graph S(VS, ES) is subgraph of graph G(VG ,EG ) if VS ? VG and ES ? EG. Work here aims to fetch all subgraphs S(VS, ES) from graph G(VG ,EG ) which are similar to query graph Q(VQ, EQ) using subgraph matching algorithm. Work carried out in two phases, offline phase and online phase. Offline phase grnertaes index over data graph G. Online phase retrieves set of subgraphs from data graph G which are similar to query graph Q. A cost function is introduced for checking similarity of query node with data graph node which efficiently reduces intermediate results by converting vertices into vector points and extracts similar subgraphs by calculating nearest distance of these vector points.