| 谭玉玲,肖媛娥.基于多目标优化的符号网络社区检测算法[J].井冈山大学自然版,2022,43(1):70-77 |
| 基于多目标优化的符号网络社区检测算法 |
| SIGNED NETWORK COMMUNITY DISCOVERY ALGORITHM BASED ON MULTI-OBJECTIVE OPTIMIZATION |
| 投稿时间：2021-03-03 修订日期：2021-05-25 |
| DOI：10.3969/j.issn.1674-8085.2022.01.012 |
| 中文关键词: 复杂网络 符号网络 社团结构 多目标优化 |
| 英文关键词: complex network signed network community structure multi-objective optimization |
| 基金项目:广东省高职高专云计算与大数据专业委员会2019年度课题（GDYJ SKT19-05）；教育部科技发展中心“天诚汇智”创新促教基金课题（2018E01020） |
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| 中文摘要: |
| 符号网络可以描述实体之间的多种关系，对符号网络中的社团检测可以挖掘出其中的有效信息。同时考虑连接密度和连接符号，将社团发现问题建模为一个多目标优化问题，基于MOEA/D框架，提出一种改进的符号网络社团发现算法，设计了基于字符串的编码方式、预分区策略、交叉合并策略、变异方式等。实验结果表明，本算法可以有效检测出社团结构。 |
| 英文摘要: |
| The signed network can describe a variety of relationships between entities, and the community detection in the signed network can dig out the effective information. At the same time, considering connection density and connection symbols, the community discovery problem is modeled as a multi-objective optimization problem. Based on the MOEA/D framework, an improved signed network community discovery algorithm is proposed, and a string-based encoding method and pre-partitioning strategy are designed. Also cross-merger strategy, mutation method are designed. The experimental results show that the algorithm can effectively detect the community structure. |
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