[1]郭茂林,孔 兵.基于 TOPSIS 权重的社会网络影响力最大化[J].计算机技术与发展,2022,32(07):15-21.[doi:10. 3969 / j. issn. 1673-629X. 2022. 07. 003]
　GUO Mao-lin,KONG Bing.Maximization of Social Network Influence Based on TOPSIS Weight[J].,2022,32(07):15-21.[doi:10. 3969 / j. issn. 1673-629X. 2022. 07. 003]
点击复制

基于 TOPSIS 权重的社会网络影响力最大化()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年07期
页码:
15-21
栏目:
大数据分析与挖掘
出版日期:
2022-07-10

文章信息/Info

Title:
Maximization of Social Network Influence Based on TOPSIS Weight
文章编号:
1673-629X(2022)07-0015-07
作者:
郭茂林; 孔 兵
云南大学 信息学院,云南 昆明 650091
Author(s):
GUO Mao-lin; KONG Bing
School of Information Science and Engineering,Yunnan University,Kunming 650091,China
关键词:
社会网络; 信息扩散; 影响力最大化; 客观权重; TOPSIS 方法
Keywords:
social networks; information diffusion; influence maximization; objective weight; TOPSIS method
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 07. 003
摘要:
识别有影响力的用户和邮件是社会网络分析中最重要的主题之一,如何寻找具有最小重叠和最大网络覆盖范围的种子节点集是社会网络研究中的一个重点问题。 针对该问题已经提出了很多算法,如贪心算法、CELF 算法、K-shell 算法和各种中心性度量排序算法等。 种子节点之间的距离越近,则节点之间的共同邻居节点越多,造成覆盖范围的重叠。目前的算法往往不考虑种子节点间的距离和其覆盖范围的重叠,导致最终的种子节点集质量不高。 该文提出了一种新方法,通过计算节点间的距离和重叠范围的综合权重,以加权的“ 优劣解距离冶 ( TOPSIS) 方法来选择有影响力的用户节点。与传统方法相比,所选择的种子节点集合有更大的影响力散布。
Abstract:
Identifying influential users and emails is one of the most important topics in social network analysis. How to find the? ?seed node set with minimum overlap and maximum network coverage is a key problem in social network research.? ?Many algorithms have been proposed to solve this problem, such as greedy algorithm, CELF algorithm, K - shell algorithm and various centrality metric sorting algorithm. The closer the distance between seed nodes, the more common neighbor nodes between nodes, resulting in overlapping coverage. Current algorithms often ignore the distance between seed nodes and the overlap of their coverage,resulting in the final seed node set of low quality. Therefore,we propose a new method that combines the objective weighting method and the TOPSIS method to select influential user nodes. This method aims to propose a solution by considering the above two goals. Compared with traditional methods,the set of seed nodes selected by the proposed method has greater influence spread.

相似文献/References:

[1]陈加忠 鞠增伟 陈常念 李榕 夏涛 王冼.基于社会网络特性的机会计算服务平台[J].计算机技术与发展,2011,(06):197.
　CHEN Jia-zhong,JU Zeng-wei,CHEN Chang-nian,et al.Opportunistic Computing Service Platform Based on Social Network Properties[J].,2011,(07):197.
[2]殷凤霞.社会网络中基于内容语义的新闻推荐方法研究[J].计算机技术与发展,2013,(10):253.
　YIN Feng-xia.Research on Method of News Recommendation Based on Content Semantic in Social Network[J].,2013,(07):253.
[3]王庚,宋传超,盛玉晓,等.基于标签传播的社区挖掘算法研究综述[J].计算机技术与发展,2013,(12):69.
　WANG Geng,SONG Chuan-chao,SHENG Yu-xiao,et al.Research Summary on Communities Mining Algorithm Based on Label Propagation[J].,2013,(07):69.
[4]王伟,李玲娟. 一种基于聚类的社团划分算法[J].计算机技术与发展,2015,25(10):119.
　WANG Wei,LI Ling-juan. A Clustering-based Community Division Algorithm[J].,2015,25(07):119.
[5]韩 婷,周丽华*,黄亚群,等.基于加权 PageRank 的异质网络影响力最大化[J].计算机技术与发展,2022,32(03):46.[doi:10. 3969 / j. issn. 1673-629X. 2022. 03. 008]
　HAN Ting,ZHOU Li-hua*,HUANG Ya-qun,et al.Influence Maximization of Heterogeneous Networks Based on Weighted PageRank[J].,2022,32(07):46.[doi:10. 3969 / j. issn. 1673-629X. 2022. 03. 008]

更新日期/Last Update: 2022-07-10