[1] |
Chen X,Pan L.A survey of graph cuts/graph search based medical image segmentation[J].IEEE Reviews in Biomedical Engineering,2018,11:112-124.
|
[2] |
Barsky A,Munzner T,Gardy J,et al.Cerebral:Visualizing multiple experimental conditions on a graph with biological context[J].IEEE Transactions on Visualization and Computer Graphics,2008,14(6):1253-1260.
|
[3] |
Nohuddin P N E,Sunayama W,Christley R,et al.Trend mining in social networks:From trend identification to visualization[J].Expert Systems,2014,31(5):457-468.
|
[4] |
Low Y,Gonzalez J,Kyrola A,et al.Distributed GraphLab:A framework for machine learning in the cloud[J].Proceedings of the VLDB Endowment,2012,5(8):716-727.
|
[5] |
Capponi A,Fiandrino C,Kliazovich D,et al.A cost-effective distributed framework for data collection in cloud-based mobile crowd sensing architectures[J].IEEE Transactions on Sustainable Computing,2017,2(1):3-16.
|
[6] |
Kernighan B W,Lin S.An efficient heuristic procedure for partitioning graphs[J].Bell System Technical Journal,1970,49(2):291-307.
|
[7] |
Barnard S T,Simon H D.Fast multilevel implementation of recursive spectral bisection for partitioning unstructured problems[J].Concurrency & Computation Practice & Experience,1994,6(2):101-117.
|
[8] |
Stanton I,Kliot G.Streaming graph partitioning for large distributed graphs[C]∥Proc of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,2012:1222-1230.
|
[9] |
Tsourakakis C,Gkantsidis C,Radunovic B,et al.FENNEL:Streaming graph partitioning for massive scale graphs[C]∥Proc of the 7th ACM International Conference on Web Search and Data Mining,2014:333-342.
|
[10] |
Nishimura J, Ugander J.Restreaming graph partitioning:Simple versatile algorithms for advanced balancing[C]∥Proc of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,2013:1106-1114.
|
[11] |
Luo Rong-zhen.Implementation of a distributed streaming graph partition system[D].Nanjing:Nanjing University,2019.(in Chinese)
|
[12] |
Zhang Meng-lin. Research on partition methods on large-scale dynamic graph based on multi-level division[D].Shen- yang:Liaoning University,2018.(in Chinese)
|
[13] |
Li Xi-jin. Streaming graph partition algorithm based on dynamic reverse mapping graph[J].Modern Computer,2018(8):89-93.(in Chinese)
|
[14] |
Lü X Q,Xiao W,Zhang Y,et al.An effective framework for asynchronous incremental graph processing[J].
|
|
Frontiers of Computer Science,2019,13:539-551.
|
[15] |
Nie Xiang-lin,Zhang Yu-mei,Wu Xiao-jun,et al.A community detection algorithm based on node dependence and similar community fusion[J].Computer Engineering & Science,2017,39(7):1273-1280.(in Chinese)
|
[16] |
Xu Jin-feng,Dong Yi-hong,Wang Shi-yi,et al.Overview of large-scale graph data partitioning algorithms [J].Telecommunications Science,2014,3(7):106-112.(in Chinese)
|
[17] |
Xu Jin-feng.Large-scale dynamic adaptive graph partitioning algorithm [D].Ningbo:Ningbo University,2015.(in Chinese)
|
|
附中文参考文献:
|
[11] |
骆融臻.分布式流式图划分系统的设计与实现[D].南京:南京大学,2019.
|
[12] |
张梦琳.基于多层次划分的大规模动态图分割方法研究[D].沈阳:辽宁大学,2018.
|
[13] |
李茜锦.基于动态反向映射图的流图划分方法[J].现代计算机,2018(8):89-93.
|
[15] |
聂祥林,张玉梅,吴晓军,等.基于节点依赖度和相似社团融合的社团结构发现算法[J].计算机工程与科学,2017,39(7):1273-1280.
|
[16] |
许金凤,董一鸿,王诗懿,等.大规模图数据划分算法综述[J].电信科学,2014,3(7):106-112.
|
[17] |
许金凤.大规模动态自适应图划分算法[D].宁波:宁波大学,2015.
|