An Improved Apriori Algorithm Based Matrix and Weight

BIAN Gen-qing; WANG Yue

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An Improved Apriori Algorithm Based Matrix and Weight

更新时间：2026-09-04

- An Improved Apriori Algorithm Based Matrix and Weight
- Vol. 34, Issue 1, Pages: 136-140(2017)
- 作者机构：
  
  西安建筑科技大学机构信息与控制工程学院,陕西,西安,710055
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
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边根庆, 王月. 一种基于矩阵和权重改进的Apriori算法[J]. 微电子学与计算机, 2017, 34(1): 136-140.

BIAN Gen-qing, WANG Yue. An Improved Apriori Algorithm Based Matrix and Weight[J]. 2017, 34(1): 136-140.
边根庆, 王月. 一种基于矩阵和权重改进的Apriori算法[J]. 微电子学与计算机, 2017, 34(1): 136-140. DOI：

BIAN Gen-qing, WANG Yue. An Improved Apriori Algorithm Based Matrix and Weight[J]. 2017, 34(1): 136-140. DOI：

摘要

提出基于矩阵和权重的一种改进算法——MW_Apriori算法.该算法首先通过扫描一次事务数据库来构造0-1事务矩阵

其次赋予项和事务权重

并计算项的权重支持度

从而得到频繁项集.实验结果表明

MW_Apriori算法避免了数据库的重复扫描

使得时间和空间的耗费显著减少

同时能有效地挖掘出隐藏的、更有价值的事件.

Abstract

An improved algorithm

which is called MW_Apriori algorithm is proposed based on the matrix and weight in this paper.Firstly

build the 0-1transaction matrix by scanning transaction database.Then items and transactions are assigned to weights

and the weighted support of items are caculated

accordingly gettig the frequent itemsets.Experiments show that MW_Apriori algorithm avoids rescanning the database

making the cost of time and space significantly reduced

at the same time can effectively mine the hidden and valuable rare events.

关键词

Keywords

references

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Muhammad Asif, Jamil Ahmed. Analysis of Effectiveness of Apriori and Frequent Pattern Tree Algorithm in Software Engineering Data Mining[C]//proceedings of 2015 6th International Conference on Intelligent Systems, Modelling and Simulation. Shanghai, 2015: 28-33.

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周发超, 王志坚, 叶枫, 等. 关联规则挖掘算法Apriori的研究改进[J]. 计算机科学与探索, 2015, 9(9): 1075-1083. DOI: 1075

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