1 |
BACKSTROM L, LESKOVEC J. Supervised random walks: predicting and recommending links in social networks [C]// Proceedings of the 4th ACM International Conference on Web Search and Data Mining. New York: ACM, 2011: 635-644. 10.1145/1935826.1935914
|
2 |
PEROZZI B, AL-RFOU R, SKIENA S. DeepWalk: online learning of social representations [C]// Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2014: 701-710. 10.1145/2623330.2623732
|
3 |
GROVER A, LESKOVEC J. Node2vec: scalable feature learning for networks [C]// Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2016: 855-864. 10.1145/2939672.2939754
|
4 |
HUANG X, SONG Q Q, LI Y N, et al. Graph recurrent networks with attributed random walks [C]// Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2019: 732-740. 10.1145/3292500.3330941
|
5 |
BORDES A, USUNIER N, GARCIA-DURÁN A, et al. Translating embeddings for modeling multi-relational data [C]// Proceedings of the 26th International Conference on Neural Information Processing Systems. Red Hook, NY: Curran Associates Inc., 2013: 2787-2795.
|
6 |
KIPF T N, WELLING M. Semi-supervised classification with graph convolutional networks[EB/OL]. (2017-02-22) [2021-04-10]. .
|
7 |
杨晓慧,万睿,张海滨,等.基于符号语义映射的知识图谱表示学习算法[J].计算机研究与发展, 2018, 55(8): 1773-1784. 10.7544/issn1000-1239.2018.20180248
|
|
YANG X H, WAN R, ZHANG H B, et al. Semantical symbol mapping embedding learning algorithm for knowledge graph[J]. Journal of Computer Research and Development, 2018, 55(8): 1773-1784. 10.7544/issn1000-1239.2018.20180248
|
8 |
NIKOLAKOPOULOS A N, KARYPIS G. RecWalk: nearly uncoupled random walks for Top-n recommendation [C]// Proceedings of the 12th ACM International Conference on Web Search and Data Mining. New York: ACM, 2019: 150-158. 10.1145/3289600.3291016
|
9 |
MEILĂ M, SHI J B. A random walks view of spectral segmentation [C]// Proceedings of the 8th International Workshop on Artificial Intelligence and Statistics. New York: JMLR.org, 2001: 203-208.
|
10 |
COOPER C, LEE S H, RADZIK T, et al. Random walks in recommender systems: exact computation and simulations [C]// Proceedings of the 23rd International Conference on World Wide Web. New York: ACM, 2014: 811-816. 10.1145/2567948.2579244
|
11 |
冶忠林,赵海兴,张科,等.基于邻节点和关系模型优化的网络表示学习[J].计算机研究与发展, 2019, 56(12): 2562-2577. 10.7544/issn1000-1239.2019.20180566
|
|
YE Z L, ZHAO H X, ZHANG K, et al. Network representation learning using the optimizations of neighboring vertices and relation model[J]. Journal of Computer Research and Development, 2019, 56(12): 2562-2577. 10.7544/issn1000-1239.2019.20180566
|
12 |
WANG Z, ZHANG J W, FENG J L, et al. Knowledge graph embedding by translating on hyperplanes [C]// Proceedings of the 28th AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2014: 1112-1119. 10.1609/aaai.v28i1.8870
|
13 |
方阳,赵翔,谭真,等.一种改进的基于翻译的知识图谱表示方法[J].计算机研究与发展, 2018, 55(1): 139-150. 10.7544/issn1000-1239.2018.20160723
|
|
FANG Y, ZHAO X, TAN Z, et al. A revised translation-based method for knowledge graph representation[J]. Journal of Computer Research and Development, 2018, 55(1): 139-150. 10.7544/issn1000-1239.2018.20160723
|
14 |
YANG B S, YIH W T, HE X D, et al. Embedding entities and relations for learning and inference in knowledge bases[EB/OL]. (2015-08-29) [2021-04-10]. .
|
15 |
TROUILLON T, WELBL J, RIEDEL S, et al. Complex embeddings for simple link prediction [C]// Proceedings of the 33rd International Conference on Machine Learning. New York: JMLR.org, 2016: 2071-2080.
|
16 |
DETTMERS T, MINERVINI P, STENETORP P, et al. Convolutional 2D knowledge graph embeddings [C]// Proceedings of the 32nd AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2018: 1811-1818. 10.1609/aaai.v32i1.11573
|
17 |
NICKEL M, ROSASCO L, POGGIO T. Holographic embeddings of knowledge graphs [C]// Proceedings of the 30th AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2016: 1955-1961. 10.1609/aaai.v30i1.10314
|
18 |
YUN S, JEONG M, KIM R, et al. Graph transformer networks[C/OL]// Proceedings of the 33rd Conference on Neural Information Processing Systems. [2021-04-10]. . 10.1016/j.neunet.2022.05.026
|
19 |
RIBEIRO L F R, SAVERESE P H P, FIGUEIREDO D R. Struc2vec: Learning node representations from structural identity [C]// Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2017: 385-394. 10.1145/3097983.3098061
|
20 |
HOU Y F, CHEN H Z, LI C J, et al. A representation learning framework for property graphs [C]// Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2019: 65-73. 10.1145/3292500.3330948
|
21 |
AHMED N K, ROSSI R A, LEE J B, et al. Role-based graph embeddings[J]. IEEE Transactions on Knowledge and Data Engineering, 2022, 34(5): 2401-2415. 10.1109/tkde.2020.3006475
|
22 |
HUANG X, LI J D, ZOU N, et al. A general embedding framework for heterogeneous information learning in large-scale networks[J]. ACM Transactions on Knowledge Discovery from Data, 2018, 12(6): No.70. 10.1145/3241063
|
23 |
MCPHERSON M, SMITH-LOVIN L, COOK J M. Birds of a feather: homophily in social networks[J]. Annual Review of Sociology, 2001, 27: 415-444. 10.1146/annurev.soc.27.1.415
|
24 |
ZHANG J, TANG J, LI J Z, et al. Who influenced you? Predicting retweet via social influence locality[J]. ACM Transactions on Knowledge Discovery from Data, 2015, 9(3): No.25. 10.1145/2700398
|