ZHANG M H, CUI Z C, JIANG S L, et al. Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space [J]. Proceedings of the AAAI Conference on Artificial Intelligence, 2018, 32(1).
PATIL P, SHARMA G, MURTY M N. Negative Sampling for Hyperlink Prediction in Networks [M] //Advances in Knowledge Discovery and Data Mining. Cham: Springer International Publishing, 2020: 607-619.
KUMAR T, DARWIN K, PARTHASARATHY S, et al. HPRA: Hyperedge Prediction Using Resource Allocation [C] //Proceedings of the 12th ACM Conference on Web Science. July 6-10, 2020, Southampton, United Kingdom. New York: ACM, 2020: 135-143.
SRINIVASAN B, ZHENG D, KARYPIS G. Learning over Families of Sets-Hypergraph Representation Learning for Higher Order Tasks [M] //Proceedings of the 2021 SIAM International Conference on Data Mining (SDM). Philadelphia, PA: Society for Industrial and Applied Mathematics, 2021: 756-764.
YUAN Y B, QU A N. High-Order Joint Embedding for Multi-Level Link Prediction [J]. Journal of the American Statistical Association, 2022: 1-15.
BENSON A R, ABEBE R, SCHAUB M T, et al. Simplicial Closure and Higher-Order Link Prediction [J]. Proceedings of the National Academy of Sciences of the United States of America, 2018, 115(48): E11221-E11230.
LORRAIN F, WHITE H C. Structural Equivalence of Individuals in Social Networks [J]. The Journal of Mathematical Sociology, 1971, 1(1): 49-80. doi: 10.1080/0022250X.1971.9989788
OU Q, JIN Y D, ZHOU T, et al. Power-Law Strength-Degree Correlation from Resource-Allocation Dynamics on Weighted Networks [J]. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 2007, 75(2 Pt 1): 021102.
KATZ L. A New Status Index Derived from Sociometric Analysis [J]. Psychometrika, 1953, 18(1): 39-43. doi: 10.1007/BF02289026
LIU Z, ZHANG Q M, LÜ L Y, et al. Link Prediction in Complex Networks: A Local Naïve Bayes Model [J]. EPL (Europhysics Letters), 2011, 96(4): 48007. doi: 10.1209/0295-5075/96/48007
吕琳媛, 周涛. 链路预测[M]. 北京: 高等教育出版社, 2013.
PAN L M, SHANG H J, LI P Y, et al. Predicting Hyperlinks via Hypernetwork Loop Structure [J]. EPL (Europhysics Letters), 2021, 135(4): 48005. doi: 10.1209/0295-5075/ac1a22
吕琳媛. 复杂网络链路预测[J]. 电子科技大学学报, 2010, 39(5): 651-661. doi: 10.3969/j.issn.1001-0548.2010.05.002
JACCARD P. Etude Comparative de La Distribution Florale Dans Une Portion des Alpes et des Jura [J]. Bull Soc Vaudoise Sci Nat, 1901, 37: 547-579.
ADAMIC L A, ADAR E. Friends and Neighbors on the Web [J]. Social Networks, 2003, 25(3): 211-230. doi: 10.1016/S0378-8733(03)00009-1
WANG Q, YAN G Y. IHRW: An Improved Hypergraph Random Walk Model for Predicting Three-Drug Therapy [J]. bioRxiv, 2021: 2021. 02. 25. 432979.
AKSOY S G, JOSLYN C, ORTIZ MARRERO C, et al. Hypernetwork Science via High-Order Hypergraph Walks [J]. EPJ Data Science, 2020, 9(1): 16. doi: 10.1140/epjds/s13688-020-00231-0
SHARMA G, PATIL P, MURTY M N. C3MM: Clique-Closure Based Hyperlink Prediction [C] //Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. July 11-17, 2020. Yokohama, Japan. California: International Joint Conferences on Artificial Intelligence Organization, 2020: 3364-3370.
SEN P, NAMATA G, BILGIC M, et al. Collective Classification in Network Data [J]. AI Magazine, 2008, 29(3): 93. doi: 10.1609/aimag.v29i3.2157
Ley M. The DBLP Computer Science Bibliography: Evolution, Research Issues, Perspectives [C] //String Processing and Information Retrieval: 9th International Symposium, SPIRE 2002 Lisbon, Portugal, September 11-13, 2002 Proceedings 9. Springer Berlin Heidelberg, 2002: 1-10.
NI J M, LI J C, MCAULEY J. Justifying Recommendations Using Distantly-Labeled Reviews and Fine-Grained Aspects [C] //Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Hong Kong, China. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019: 188-197.
YIN H, BENSON A R, LESKOVEC J, et al. Local Higher-Order Graph Clustering [C] //Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. August 13-17, 2017, Halifax, NS, Canada. New York: ACM, 2017: 555-564.
LESKOVEC J, KLEINBERG J, FALOUTSOS C. Graph Evolution: Densification and Shrinking Diameters [J]. ACM Transactions on Knowledge Discovery from Data, 2007, 1(1): 2-es. doi: 10.1145/1217299.1217301
GHASEMIAN A, HOSSEINMARDI H, GALSTYAN A, et al. Stacking Models for nearly Optimal Link Prediction in Complex Networks [J]. Proceedings of the National Academy of Sciences of the United States of America, 2020, 117(38): 23393-23400. doi: 10.1073/pnas.1914950117
KOVÁCS I A, LUCK K, SPIROHN K, et al. Network-Based Prediction of Protein Interactions [J]. Nature Communications, 2019, 10(1): 1240. doi: 10.1038/s41467-019-09177-y
ZHANG Z K, LIU C A. A Hypergraph Model of Social Tagging Networks [J]. Journal of Statistical Mechanics: Theory and Experiment, 2010, 2010(10): P10005. doi: 10.1088/1742-5468/2010/10/P10005
CARLETTI T, BATTISTON F, CENCETTI G, et al. Random Walks on Hypergraphs [J]. Physical Review E, 2020, 101(2): 022308.
HWANG H, LEE S, PARK C, et al. AHP: Learning to Negative Sample for Hyperedge Prediction [C] //Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. July 11-15, 2022, Madrid, Spain. New York: ACM, 2022: 2237-2242.
YANG D Q, QU B Q, YANG J, et al. Revisiting User Mobility and Social Relationships in LBSNS: A Hypergraph Embedding Approach [C] //WWW '19: The World Wide Web Conference. May 13-17, 2019, San Francisco, CA, USA. New York: ACM, 2019: 2147-2157.