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Group interactions arise in our daily lives (email communications, on-demand ride sharing, comment interactions on online communities, to name a few), and they together form hypergraphs that evolve over time.
S. P. Borgatti and M. G. Everett, “Network analysis of 2-mode data,” Social networks , vol. 19, no. 3, pp. 243–269, 1997
1997
Earlier work this paper cites.
R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, and U. Alon, “Network motifs: simple building blocks of complex networks,” Science , vol. 298, no. 5594, pp. 824–827, 2002
2002
Earlier work this paper cites.
S. S. Shen-Orr, R. Milo, S. Mangan, and U. Alon, “Network motifs in the transcriptional regulation network of escherichia coli,” Nature Genetics , vol. 31, no. 1, pp. 64–68, 2002
2002
Earlier work this paper cites.
R. Milo, S. Itzkovitz, N. Kashtan, R. Levitt, S. Shen-Orr, I. Ayzenshtat, M. Sheffer, and U. Alon, “Superfamilies of evolved and designed networks,” Science , vol. 303, no. 5663, pp. 1538–1542, 2004
2004
Earlier work this paper cites.
A. Arenas, A. Fernandez, S. Fortunato, and S. Gomez, “Motif-based communities in complex networks,” Journal of Physics A: Math Theor. , vol. 41, no. 22, p. 224001, 2008
2008
Earlier work this paper cites.
L. Kovanen, M. Karsai, K. Kaski, J. Kertész, and J. Saramäki, “Temporal motifs in time-dependent networks,” Journal of Statistical Mechanics: Theory and Experiment , vol. 2011, no. 11, p. P11005, 2011
2011
Earlier work this paper cites.
U. Redmond and P. Cunningham, “Temporal subgraph isomorphism,” in ASONAM , 2013
2013
Earlier work this paper cites.
S. Gurukar, S. Ranu, and B. Ravindran, “Commit: A scalable approach to mining communication motifs from dynamic networks,” in SIGMOD , 2015
2015
Earlier work this paper cites.
A. R. Benson, D. F. Gleich, and J. Leskovec, “Higher-order organization of complex networks,” Science , vol. 353, no. 6295, pp. 163–166, 2016
2016
Earlier work this paper cites.
A. Paranjape, A. R. Benson, and J. Leskovec, “Motifs in temporal networks,” in WSDM , 2017
2017
Earlier work this paper cites.
C. E. Tsourakakis, J. Pachocki, and M. Mitzenmacher, “Scalable motif-aware graph clustering,” in WWW , 2017
2017
Cited alongside, same era.
H. Yin, A. R. Benson, J. Leskovec, and D. F. Gleich, “Local higher-order graph clustering,” in KDD , 2017
2017
Cited alongside, same era.
A. R. Benson, R. Kumar, and A. Tomkins, “Sequences of sets,” in KDD , 2018
2018
Cited alongside, same era.
A. R. Benson, R. Abebe, M. T. Schaub, A. Jadbabaie, and J. Kleinberg, “Simplicial closure and higher-order link prediction,” Proceedings of the National Academy of Sciences , vol. 115, no. 48, pp. E11 221–E11 230, 2018
2018
Cited alongside, same era.
Y. Li, Z. Lou, Y. Shi, and J. Han, “Temporal motifs in heterogeneous information networks,” in MLG Workshop , 2018
2018
Cited alongside, same era.
J. B. Lee, R. A. Rossi, X. Kong, S. Kim, E. Koh, and A. Rao, “Graph convolutional networks with motif-based attention,” in CIKM , 2019
2019
Later among the works it cites.
Y. Kook, J. Ko, and K. Shin, “Evolution of real-world hypergraphs: Patterns and models without oracles,” in ICDM , 2020
2020
Later among the works it cites.
M. T. Do, S.-e. Yoon, B. Hooi, and K. Shin, “Structural patterns and generative models of real-world hypergraphs,” in KDD , 2020
2020
Later among the works it cites.
G. Lee, J. Ko, and K. Shin, “Hypergraph motifs: concepts, algorithms, and discoveries,” PVLDB , vol. 13, pp. 2256–2269, 2020
2020
Later among the works it cites.
S.-e. Yoon, H. Song, K. Shin, and Y. Yi, “How much and when do we need higher-order information in hypergraphs? a case study on hyperedge prediction,” in WWW , 2020
2020
Later among the works it cites.
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H. Zhao, X. Xu, Y. Song, D. L. Lee, Z. Chen, and H. Gao, “Ranking users in social networks with higher-order structures,” in AAAI , 2018
2018
Cited alongside, same era.
R. A. Rossi, N. K. Ahmed, and E. Koh, “Higher-order network representation learning,” in WWW Companion , 2018
2018
Cited alongside, same era.
R. A. Rossi, R. Zhou, and N. K. Ahmed, “Deep inductive graph representation learning,” IEEE TKDE , vol. 32, no. 3, pp. 438–452, 2018
2018
Cited alongside, same era.
P.-Z. Li, L. Huang, C.-D. Wang, and J.-H. Lai, “Edmot: An edge enhancement approach for motif-aware community detection,” in KDD , 2019
2019
Cited alongside, same era.
Y. Yu, Z. Lu, J. Liu, G. Zhao, and J.-r. Wen, “Rum: Network representation learning using motifs,” in ICDE , 2019
2019
Cited alongside, same era.
R. A. Rossi, N. K. Ahmed, A. Carranza, D. Arbour, A. Rao, S. Kim, and E. Koh, “Heterogeneous graphlets,” ACM TKDD , vol. 15, no. 1, pp. 1–43, 2020
2020
Later among the works it cites.
R. A. Rossi, N. K. Ahmed, E. Koh, S. Kim, A. Rao, and Y. Abbasi-Yadkori, “A structural graph representation learning framework,” in WSDM , 2020
2020
Later among the works it cites.
G. Lee, M. Choe, and K. Shin, “How do hyperedges overlap in real-world hypergraphs?–patterns, measures, and generators,” in WWW , 2021
2021
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