Efficient Multi-relational Bayesian Classification Algorithm

DENG Zuo-xiang; TU Fang

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Efficient Multi-relational Bayesian Classification Algorithm

更新时间：2026-09-04

- Efficient Multi-relational Bayesian Classification Algorithm
- Vol. 34, Issue 7, Pages: 123-127(2017)
- 作者机构：
  
  1. 广西科技大学计算机科学与通信工程学院,广西,柳州,545006
  2. 广西科技大学机构智能计算与分布式信息处理重点实验室培育基地,广西,柳州,545006
  3. 上海交通大学电子信息与电气工程学院,上海,200240
  4. 上汽通用五菱汽车股份有限公司技术中心产品认证科,广西,柳州,545007
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
移动端阅览
邓左祥, 涂芳. 一种有效的多关系贝叶斯分类算法[J]. 微电子学与计算机, 2017, 34(7): 123-127.

DENG Zuo-xiang, TU Fang. Efficient Multi-relational Bayesian Classification Algorithm[J]. 2017, 34(7): 123-127.
邓左祥, 涂芳. 一种有效的多关系贝叶斯分类算法[J]. 微电子学与计算机, 2017, 34(7): 123-127. DOI：

DENG Zuo-xiang, TU Fang. Efficient Multi-relational Bayesian Classification Algorithm[J]. 2017, 34(7): 123-127. DOI：

摘要

传统数据挖掘算法在处理多关系时

需要物理连接

因此存在效率不高的问题.为了解决这一问题

研究多关系数据挖掘中的分类问题

提出一种有效的多关系贝叶斯分类算法EMBC.EMBC算法的目标是提高分类的准确率

并且降低运行时间.EMBC算法利用元组ID传播的思想

结合朴素贝叶斯分类算法

可以直接在多关系上进行分类.实验表明

EMBC算法提高分类的准确率

并且显著降低运行时间.

Abstract

While dealing with multi-relation

traditional data mining algorithms used physical join

thus it had the problem of low efficiency. In order to solve this problem

the problem of classification in multi-relational data mining was investigated

and an efficient multi-relational Bayesian classification algorithm called EMBC was proposed. EMBC aims at increasing the accuracy of classification

and decreasing running time. By taking advantage of tuple ID propagation approach

and combined with naive Bayesian classification algorithm

EMBC can directly classify in multi-relation. Performance results demonstrate that

EMBC increases the accuracy of classification

and significantly decreases running time.

关键词

Keywords

references

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徐光美, 刘宏哲, 张敬尊. 基于特征加权的多关系朴素贝叶斯分类模型[J]. 计算机科学, 2014, 41(10): 283-285. DOI: 283

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Related Author

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Related Institution

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