1 |
竺俊超, 王朝坤. 复杂条件下的社区搜索方法[J]. 软件学报, 2019, 30(3): 552 - 572.
|
|
ZHUJun-chao, WANGChao-kun. Approaches to community search under complex conditions[J]. Journal of Software, 2019, 30(3): 552 - 572. (in Chinese)
|
2 |
潘剑飞, 董一鸿, 陈华辉, 等. 基于结构紧密性的重叠社区发现算法[J]. 电子学报, 2019, 47(1): 145 - 152.
|
|
PANJian-fei,DONGYi-hong,CHENHua-hui,et al. The overlapping community discovery algorithm based on compact structure [J]. Acta Electronica Sinica, 2019, 47(1): 145 - 152. (in Chinese)
|
3 |
WangZ Z, YuanY, ZhouX M, et al. Effective and efficient community search in directed graphs across heterogeneous social networks[A]. Proceedings of the 31st Australasian Database Conference[C]. Melbourne, Australia: Springer, 2020. 161 - 172.
|
4 |
LiuS, XiaZ. A two-stage BFS local community detection algorithm based on node transfer similarity and local clustering coefficient[J]. Physica A: Statistical Mechanics and its Applications, 2020, 537: 122717.
|
5 |
AndersenR, ChungF, LangK. Local graph partitioning using pagerank vectors[A]. Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science[C]. Berkeley, CA, USA: IEEE, 2006. 475 - 486.
|
6 |
BianY, LuoD, YanY, et al. Memory-based random walk for multi-query local community detection[J]. Knowledge and Information Systems, 2020, 62(5): 2067 - 2101.
|
7 |
HsuC C, LaiY A, ChenW H, et al. Unsupervised ranking using graph structures and node attributes[A]. Proceedings of the 10th International Conference on Web Search and Data Mining[C]. Cambridge, UK: ACM, 2017. 771 - 779.
|
8 |
FreitasS, CaoN, XiaY L, et al. Local partition in rich graphs[A]. Proceedings of the 2018 IEEE International Conference on Big Data[C]. Seattle, USA: IEEE, 2018. 1001 - 1008.
|
9 |
LancichinettiA, FortunatoS, RadicchiF. Benchmark graphs for testing community detection algorithms[J]. Physical review E, 2008, 78(4): 046110.
|
10 |
刘海姣, 马慧芳, 赵琪琪, 李志欣. 融合用户兴趣偏好与影响力的目标社区发现[J]. 计算机研究与发展, 2021, 58(1): 70 - 82.
|
|
LIUHai-jiao, MAHui-fang, ZHAOQi-qi, LIZhi-xin. Target community detection with user interest influence[J]. Journal of Computer Research and Development, 2021, 58(1): 70 - 82. (in Chinese)
|
11 |
BianY, NiJ, ChengW, ZhangX. The multi-walker chain and its application in local community detection[J]. Knowledge and Information Systems, 2019, 60(3): 1663 - 1691.
|
12 |
YeW, MautzD, et al. Incorporating user’s preference into attributed graph clustering[J]. IEEE Transactions on Knowledge and Data Engineering, 2020. DOI:10.1109/TKDE.2020.2976063.
|
13 |
KamuhandaD, WangM, HeK. Sparse nonnegative matrix factorization for multiple-local-community detection[J]. IEEE Transactions on Computational Social Systems, 2020, 7(5): 1220 - 1233.
|
14 |
DingX, ZhangJ, YangJ. A robust two-stage algorithm for local community detection[J]. Knowledge-Based Systems, 2018, 152: 188 - 199.
|