cgSpan: Closed Graph-Based Substructure Pattern Mining

TL;DR

cgSpan is an extension of gSpan that efficiently mines closed subgraphs in graph databases by incorporating an Early Termination pruning method, providing the first publicly available implementation for this task.

Contribution

It introduces cgSpan, a novel algorithm that extends gSpan with pruning techniques for closed subgraph mining, and offers the first public implementation.

Findings

cgSpan outperforms gSpan in mining efficiency.

Successfully mines closed subgraphs with pruning techniques.

Provides the first public implementation for closed graph mining.

Abstract

gSpan is a popular algorithm for mining frequent subgraphs. cgSpan (closed graph-based substructure pattern mining) is a gSpan extension that only mines closed subgraphs. A subgraph g is closed in the graphs database if there is no proper frequent supergraph of g that has equivalent occurrence with g. cgSpan adds the Early Termination pruning method to the gSpan pruning methods, while leaving the original gSpan steps unchanged. cgSpan also detects and handles cases in which Early Termination should not be applied. To the best of our knowledge, cgSpan is the first publicly available implementation for closed graphs mining