Crystal is a novel method for distributed subgraph matching on very large graphs. Crystal outperforms existing methods by several orders of magnitude on very large graphs. The work was published on VLDB 2018 with title "Subgraph matching: on compression and computation".
The repo lists papers of various areas, including Graph Analytics, Graph Acceleration, Subgraph Matching, Streaming Graph Management, Worst-case Optimal Join Algorithms, Join Plan Optimization, and so on.
Distributed Subgraph Enumeration via Backtracking-based Framework
Source Code: Sub-GMN: Subgraph Matching Network
This is the code of "Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing System".
C++ (Boost) implementation of Subgraph retrieval from given set of graphs
This repository contains a JavaScript algorithm designed to compare two graphs and identify the largest subgraph while calculating its critical path. Developed as a project for a course in my master's program, this project delves into discrete structures and graph theory, offering practical insights into graph analysis and optimization
Source code of "RapidFlow: An Efficient Approach to Continuous Subgraph Matching" published in VLDB'2022 - By Shixuan Sun, Xibo Sun, Bingsheng He and Qiong Luo
Source code and datasets of "An In-Depth Study of Continuous Subgraph Matching", accepted by VLDB'22 - By Xibo Sun, Dr. Shixuan Sun, Prof. Qiong Luo, and Prof. Bingsheng He
Neural Subgraph Matching Paper: "AEDNet: Adaptive Edge-Deleting Network For Subgraph Matching". [Neural-Subgraph-Matching Method For Learning-Subgraph-Matching. (Approximate Subgraph matching, SubgraphMatching)]
Source code and datasets of "Efficient GPU-Accelerated Subgraph Matching", accepted by SIGMOD'23 - By Xibo Sun and Prof. Qiong Luo
In-Memory Subgraph Matching: An In-depth Study by Dr. Shixuan Sun and Prof. Qiong Luo
in-depth analysis and comparison of eight leading in-memory subgraph matching algorithms, QuickSI, GraphQL, CFL, CECI, DP-iso, RI, and VF2++.
Python and LaTeX code for my master's thesis on the topic "Complexity and Algorithms for Weighted Subgraphs"
Running benchmarks (including BI 3/4/10/11/13/14) to compare the performance with or without indexed edges of LDBC-SNB dataset via VEQ algorithm.
Approximate Subgraph Matching on Large, Dynamic Graphs.
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