graph-similarity

A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).

A scikit-learn compatible library for graph kernels

A python library to compute the graph Ricci curvature and Ricci flow on NetworkX graph.

Implementation of IROS20 paper - "Semantic Graph Based Place Recognition for 3D Point Clouds"

H2MN: Graph Similarity Learning with Hierarchical Hypergraph Matching Networks (KDD-2021)

Keras implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation". Includes synthetic GED data.

Slides and code for the Morgan Claypool book on "Individual and Collective Graph Mining: Principles, Algorithms and Applications"

A library for finding the maximum common induced subgraph between two graphs and compute their similarity (correlation).

Quantifying Pairwise Chemical Similarity for Polymers

This repository provides a Matlab implementation of MP-SimRank, a graph-based framework that models multiple perspective of similarity in the data

This is a friend recommendation systems which are used on social media platforms (e.g. Facebook, Instagram, Twitter) to suggest friends/new connections based on common interests, workplace, common friends etc. using Graph Mining techniques. Here, we are given a social graph, i.e. a graph structure where nodes are individuals on social media platforms and a directed edges (or 'links') indicates that one person 'follows' the other, or are 'friends' on social media. Now, the task is to predict newer edges to be offered as 'friend suggestions'.

Multi-Relational Graph Transformer for Automatic Short Answer Grading (NAACL 2022)

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation [WSDM-2019]

A Julia package for kernel functions on graphs

Graph Letter Editor for Jobs on Letter Recognition using Graphs Similarity

Python code to find the the Approximate Graph Edit Distance of two unit Java functions by analyzing their Control Flow Graphs

Graph Similarity and Resilience Ranking

Analysis of methods for efficient graph similarity joins over different types of graphs