Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Hongchao Qin"'
Publikováno v:
International Journal of Software & Informatics; 2023, Vol. 13 Issue 4, p379-397, 19p
Publikováno v:
IEEE Transactions on Big Data. 9:37-50
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27b3fa9b64834a0ff0e4b44a29f0a94a
https://doi.org/10.1109/tbdata.2021.3093355
https://doi.org/10.1109/tbdata.2021.3093355
Autor:
Guoren Wang, Yue Zeng, Rong-Hua Li, Hongchao Qin, Xuanhua Shi, Yubin Xia, Xuequn Shang, Liang Hong
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cb90e456ac9451743be0d09ae42c5ef
https://doi.org/10.1109/tkde.2023.3270460
https://doi.org/10.1109/tkde.2023.3270460
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe88dc120d9138d595d8878b5dba6518
https://doi.org/10.1109/tkde.2022.3233788
https://doi.org/10.1109/tkde.2022.3233788
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:3927-3945
Mining periodic communities are essential to understanding periodic group behaviors in temporal networks. Unfortunately, most previous studies for community mining in temporal networks ignore the periodic patterns of communities. In this paper, we st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43fec5eef501a8959c9f881ee066ec57
https://doi.org/10.1109/tkde.2020.3028025
https://doi.org/10.1109/tkde.2020.3028025
Publikováno v:
IEEE Transactions on Big Data. 8:671-684
Community detection is a fundamental task in graph data mining. Most existing studies in contact networks, collaboration networks, and social networks do not utilize the temporal information associated with edges for community detection. In this pape
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40fe1574db7e9295339c725da2ca442e
https://doi.org/10.1109/tbdata.2020.2974849
https://doi.org/10.1109/tbdata.2020.2974849
Publikováno v:
Web and Big Data ISBN: 9783031251573
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d571d0bffd0cd7cb9a0a98be1ca46f47
https://doi.org/10.1007/978-3-031-25158-0_38
https://doi.org/10.1007/978-3-031-25158-0_38
Autor:
Zijian Chen, Rong-Hua Li, Hongchao Qin, Huanzhong Duan, Yanxiong Lu, Qiangqiang Dai, Guoren Wang
Publikováno v:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
Graph kernels and graph neural networks (GNNs) are widely used for the classification of graph data. However, many existing graph kernels and GNNs have limited expressive power, because they cannot distinguish graphs if the classic 1-dimensional Weis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7383002ae05c4310724863455ebb01c2
https://doi.org/10.24963/ijcai.2022/276
https://doi.org/10.24963/ijcai.2022/276
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0020c1fbbc1dd29a9ad911786e9886d5
https://doi.org/10.1109/icde53745.2022.00239
https://doi.org/10.1109/icde53745.2022.00239
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030394684
ADC
ADC
Communities in social networks are useful for many real applications, like product recommendation. This fact has driven the recent research interest in retrieving communities online. Although certain effort has been put into community search, users
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61e2cb1432f89047c9d36e077392e4a1
https://doi.org/10.1007/978-3-030-39469-1_13
https://doi.org/10.1007/978-3-030-39469-1_13