# Frequent Itemset Mining using QUBO

## TL;DR

This paper introduces a quantum computing approach to frequent itemset mining by approximating the problem as a maximum clique problem suitable for quantum annealing or QAOA, aiming to leverage quantum hardware for data mining tasks.

## Contribution

It presents a novel R-step approximation method that reformulates frequent itemset mining as a maximum clique problem for quantum hardware implementation.

## Key findings

- Demonstrates the feasibility of quantum-based frequent itemset mining
- Provides a new approximation technique for quantum algorithms
- Links data mining with quantum maximum clique problem

## Abstract

In this paper we propose a R-step approximation to solve frequent itemset mining on quantum hardware like quantum annealing or QAOA. The idea is to search for the set of items where the minimal 2-item frequency is maximal. This can be represented as a maximum clique problem.

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Source: https://tomesphere.com/paper/1904.07693