摘要
为适应当前动态网络数据的发展,对动态网络中的社团结构进行检测、追踪和预测,对国内外关于动态网络社团发现与演化的相关文献进行了综述。归纳了动态网络的社团发现算法,清晰了社团演化事件的定义,并梳理了社团发现与演化算法的应用场景。通过文献梳理,提出将来动态社团的研究应注重在大数据集上的算法优化、在多语境下的信息挖掘和在多场景下的应用性。
In order to adapt to the development of dynamic network data,the detection,tracking and prediction of the community structure in dynamic networks have been a crucial research problem at present.This research reviewed the literatures on community discovery and community evolution in dynamic networks at home and abroad.This research summarized the community discovery algorithm of dynamic network,clarified the definitions of community evolution events,and sorted out the application scenarios of community evolution algorithm.Through literature review,it is believed that future dynamic community research should focus on algorithm optimization on large data sets,data mining in multiple contexts,and applicability in multiple scenarios.
作者
李永宁
吴晔
张伦
LI Yongning;WU Ye;ZHANG Lun(School of Systems Science,Beijing 100875,China;Center for Computational Communication Research,Zhuhai 519085,China;School of Journalism and Communication,Beijing 100875,China;School of Arts&Communication,Beijing Normal University,Beijing 100875,China)
出处
《复杂系统与复杂性科学》
CAS
CSCD
北大核心
2021年第2期1-8,88,共9页
Complex Systems and Complexity Science
基金
国家自然科学基金面上项目(11875005)
教育部人文社会科学研究青年基金项目(16YJC630022)
国家哲学社会科学基金一般项目(20BXW102)。
关键词
动态网络
社团发现
社团演化
dynamic networks
community detection
community evolution
