Community Division Method in Networks Based on Moderately Greedy Algorithm

WU Peng; WANG Heng-shan

Chinese

您当前的位置：

首页 >

文章列表页 >

Community Division Method in Networks Based on Moderately Greedy Algorithm

更新时间：2026-09-04

- Community Division Method in Networks Based on Moderately Greedy Algorithm
- Vol. 31, Issue 7, Pages: 101-104(2014)
- 作者机构：
  
  1. 上海理工大学机构管理学院,上海,200093
  2. 河南大学机构软件学院,河南,开封,475001
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
移动端阅览
武澎, 王恒山. 一种基于适度贪心算法思路的社团划分改进方法[J]. 微电子学与计算机, 2014, 31(7): 101-104.

WU Peng, WANG Heng-shan. Community Division Method in Networks Based on Moderately Greedy Algorithm[J]. 2014, 31(7): 101-104.
武澎, 王恒山. 一种基于适度贪心算法思路的社团划分改进方法[J]. 微电子学与计算机, 2014, 31(7): 101-104. DOI：

WU Peng, WANG Heng-shan. Community Division Method in Networks Based on Moderately Greedy Algorithm[J]. 2014, 31(7): 101-104. DOI：

摘要

当前问题背景下贪心算法存在不足

由此提出一种适度贪心的算法思路

引入适度原则

约束贪婪幅度

以避免过度贪婪、谬误累积的情况

并将适度贪心算法思路应用于FN社团划分算法的改进研究

构建了一种新的网络社团区划算法.通过算例对提出的算法进行了测试与分析

实验结果验证了新算法的可行性与有效性.

Abstract

This paper

based on the deficiency of greedy algorithm

tries to propose a new algorithmic thinking from the perspective of the moderate principle.The moderate principle can avoid the occurrence of excessive greed situation.Based on the lack of FN algorithm

this paper proposes a new algorithm to divide community structure from the perspective of the moderately greedy algorithm.Finally

the new algorithm is illustrated through examples.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on assembly action recognition based on MSS-YOLO-MPHands fusion architecture

A review of large model development: technological evolution from BERT to Deepseek

A high-efficiency charge pump for ultra-low voltage boost systems

Simulation on the DC characteristics of double heterojunction p-GaN HEMT with AlN/GaN hybrid buffer layer

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰