Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Yexuan Shi"'
Publikováno v:
大数据, Vol 9, Pp 32-43 (2023)
k-dominant skyline is a prevailing skyline query which has widespread applications in multi-criteria decision making and recommendation.As these applications continuously scale up, there is an increasing demand to support k-dominant skyline over a da
Externí odkaz:
https://doaj.org/article/c6320e1457cb4c999c2354bf2c26a5c1
Publikováno v:
ICDE
Dynamic ridesharing refers to services that arrange one-time shared rides on short notice. It underpins various real-world intelligent transportation applications such as car-pooling, food delivery and last-mile logistics. A core operation in dynamic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9fb17950f635381246a8a4ed468b24f
https://doi.org/10.1109/tkde.2020.3027200
https://doi.org/10.1109/tkde.2020.3027200
Autor:
Xuchen Pan, Yongxin Tong, Chunbo Xue, Zimu Zhou, Junping Du, Yuxiang Zeng, Yexuan Shi, Xiaofei Zhang, Lei Chen, Yi Xu, Ke Xu, Weifeng Lv
Publikováno v:
Xiaofei Zhang
The increasing concerns on data security limit the sharing of data distributedly stored at multiple data owners and impede the scale of spatial queries over big urban data. In response, data federation systems have emerged to perform secure queries a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f35df9e3bdd99335f7ed396bfa604ee1
https://doi.org/10.14778/3554821.3554849
https://doi.org/10.14778/3554821.3554849
Autor:
Yongxin Tong, Xuchen Pan, Yuxiang Zeng, Yexuan Shi, Chunbo Xue, Zimu Zhou, Xiaofei Zhang, Lei Chen, Yi Xu, Ke Xu, Weifeng Lv
Publikováno v:
Xiaofei Zhang
Data isolation has become an obstacle to scale up query processing over big data, since sharing raw data among data owners is often prohibitive due to security concerns. A promising solution is to perform secure queries over a federation of multiple
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a04a647efb945bc601d212e7c4f7ac0
https://doi.org/10.14778/3514061.3514064
https://doi.org/10.14778/3514061.3514064
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::354ce523a788aeddfa6226745902f163
https://doi.org/10.1109/tkde.2022.3222415
https://doi.org/10.1109/tkde.2022.3222415
Autor:
Kaining Zhang, Yongxin Tong, Yexuan Shi, Yuxiang Zeng, Yi Xu, Lei Chen, Zimu Zhou, Ke Xu, Weifeng Lv, Zhiming Zheng
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783031306365
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd28fffe830a13201f6b14643059d314
https://doi.org/10.1007/978-3-031-30637-2_23
https://doi.org/10.1007/978-3-031-30637-2_23
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ecaec4fb071eb50be67b46648946b1cc
https://doi.org/10.1109/bigdata55660.2022.10020254
https://doi.org/10.1109/bigdata55660.2022.10020254
Publikováno v:
IEEE Intelligent Systems. 36:96-103
General-purpose topic models have widespread industrial applications. Yet high-quality topic modeling is becoming increasingly challenging because accurate models require large amounts of training data typically owned by multiple parties, who are oft
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d36ffaea4918159b067b88577843336
https://doi.org/10.1109/mis.2020.3033459
https://doi.org/10.1109/mis.2020.3033459
Efficient Approximate Range Aggregation over Large-scale Spatial Data Federation (Extended Abstract)
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dbbd9a6fa805d0ccc887c89cf60667cc
https://doi.org/10.1109/icde53745.2022.00156
https://doi.org/10.1109/icde53745.2022.00156
Publikováno v:
International Journal of Software & Informatics; 2023, Vol. 13 Issue 1, p117-137, 21p