中南民族大学学报（自然科学版）2024，Vol.43Issue(3)：358-369,12.DOI:10.20056/j.cnki.ZNMDZK.20240310
灵活的属性社区搜索方法
Flexible community search approaches over attribute graph
摘要
Abstract
Community search aims to search for communities that satisfy specified conditions,and has a wide range of applications in the real world.The problem of community search in attribute graphs is studied.Considering the need to limit the number of vertices in a community in practical applications,a flexible attribute community search problem is proposed,whose goal is to find the subgraph with maximum graph attribute scores among connected subgraphs containing the query node with limited node sizes.Different from the traditional community search problem,a parameter-free community model is adpoted to measure the closeness of the community,thus avoiding the difficulty of specifying parameters and making the query more flexible.Three algorithms are proposed,i.e.,exact algorithm EXACT,heuristic algorithm FACH and optimization algorithm FACH+.In FACH and FACH+,the research designs the pruning rule and modifies the heuristic strategy appropriately in FACH+,which can find the subgraphs that meet the requirements quickly and efficiently.The results of experiments on several real social network datasets show that the algorithms proposed in this paper have significant advantages in both accuracy and efficiency.关键词
社交网络/社区搜索/属性图Key words
social network/community search/attribute graph分类
信息技术与安全科学引用本文复制引用
姚静怡,李艳红,黄银峰,罗昌银..灵活的属性社区搜索方法[J].中南民族大学学报（自然科学版）,2024,43(3):358-369,12.基金项目
湖北省自然科学基金资助项目(2017CFB135) （2017CFB135）
中央高校基本科研业务费专项资金资助项目(CZY23019) （CZY23019）
