The shortest yet efficient Python implementation of the sequential pattern mining algorithm PrefixSpan, closed sequential pattern mining algorithm BIDE, and generator sequential pattern mining algorithm FEAT.

PAMI is a Python library containing 100+ algorithms to discover useful patterns in various databases across multiple computing platforms. (Active)

[AAAI 2022] Seq2Pat: Sequence-to-Pattern Generation Library

Graph Pattern Mining

scikit-mine : pattern mining in Python

Python SPMF Wrapper 🐍 🎁

A visualization tool that supports queries and pattern mining for event sequence exploration

This is an automated transformation inference tool that leverages a big code corpus to guide the abstraction of transformation patterns.

A Java Desktop application with a graphical user interface for the discovery of colinear syntenic blocks across thousands microbial genomes

Mining Relevant Fix Patterns for Automated Program Repair

RuleMiner is a package for data mining in Julia with support for itemset and association rule mining algorithms

LoCoMotif is a time series motif discovery method that discovers variable-length motif sets in multivariate time series using time warping

Vertex Ordering to List Triangles: a fast C++ tool for triangle counting or listing in big graphs. See associated paper: https://arxiv.org/abs/2203.04774

Higher-order genetic interaction discovery with network-based biological priors.

Pattern Mining for the Classification of Public Procurement Fraud

Describe data in terms of informative and concise sets of patterns

Exceptional Model Mining is a descriptive data mining technique to find interesting patterns in datasets. This package contains a Python inmplementation of Exceptional Model Mining that can be applied to any dataset.

The shortest yet efficient implementation of the famous sequential pattern mining algorithm PrefixSpan in Scala.

C# code of ECSM (AI 2016 conference)

This repo is created to perform I/O Request Packet (IRP) driven ransomware analysis where the IRP logs were collected during ransomware execution.