粒子群优化算法在关联规则挖掘中的研究综述

关联规则挖掘是数据挖掘中的重要领域,考虑到当前数据的大规模、高维度、模态多样及类型复杂等特性,传统关联规则挖掘算法已无法适应大数据的需求,粒子群优化算法作为一种高效的智能优化算法,为其提供了一种全新的解决方案,近年来被广泛应用于该领域.首先对粒子群优化算法的基本原理及关联规则的基本概念进行了详细介绍,回顾了粒子群优化算...

Survey of Particle Swarm Optimization Algorithm for Association Rule Mining

Association rule mining is an important area in data mining,considering the large scale,high dimensionality,modal diversity and type complexity of current data,traditional association rule mining algorithms cannot meet the needs of big data.The particle swarm optimization algorithm,as an efficient intelligent algorithm,provides a new solution and has been widely used in association rule mining field in recent years.This paper introduces the basic principle of swarm optimization algorithm and the basic concept of association rules,and reviews the research progress of the swarm optimization algorithm itself.Then,this paper further summarizes the researches of the swarm optimization algorithm in association rule mining problem,including common data conversion methods,coding methods,and evaluation indexes.These improved algorithms from related researches are compared with other algorithms widely used in association rule mining,and their advantages,disadvantages,and application scenarios are discussed.After that,the existing improvement algorithms are systematically classified according to its methods,such as parameter,variation,and hybrid algorithm improvements,and the application areas of particle swarm optimization algorithms in association rule mining are also summarized,such as shopping baskets,finances,medical,industrial productions and risk assessments.At last,based on the introduction of the latest research progress in this field,further research directions are discussed by analyzing the existing problems.