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关联规则挖掘算法综述

Summary of Association Rules Mining Algorithms

中文摘要英文摘要

关联规则挖掘是数据挖掘的重要研究领域之一。本文首先全面地关联规则的基本概念,包括项目、交易、支持度、置信度等,然后介绍了关联规则挖掘的步骤、常用性质及其分类方法,最后介绍了关联规则挖掘的研究现状。关联规则挖掘算法目前已经有了广泛的研究,主要的研究方向有经典布尔关联规则算法的优化、多维和多层关联规则的进一步研究、关联规则的增量更新算法、基于频繁项集的规则挖掘、特殊模式类型的关联规则和关联规则挖掘在特殊领域中的应用等。

ssociation rule mining is one of the important research areas of data mining. This paper firstly comprehensively introduces the basic concepts of association rules, including Item, transaction, support, confidence, etc., and then describes the steps of association rule mining, its property, and a classification method used, and finally introduces the research status of association rule mining. Association rule mining algorithms have been extensively studied at present, the main research direction including the optimization of classical Boolean association rules algorithm, further study in multidimensional and multilevel association rules, incremental updating algorithm of association rules, rules mining based on frequent item sets, special model types of association rules and applications of association rules in special fields.

孟凡荣、姜丽莉

计算技术、计算机技术

关联规则数据挖掘频繁项集

association rulesdata miningfrequent item sets

孟凡荣,姜丽莉.关联规则挖掘算法综述[EB/OL].(2011-01-11)[2025-08-16].http://www.paper.edu.cn/releasepaper/content/201101-532.点此复制

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