Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Huiting Hong"'
Publikováno v:
IEEE Access, Vol 7, Pp 26268-26277 (2019)
Efficient and economic parcel delivery becomes a key factor in the success of online shopping. Addressing this challenge, this paper proposes to crowdsource the parcel delivery task to urban vehicles to utilize their spare capacities, thus improving
Externí odkaz:
https://doaj.org/article/cfb76c9edf8c4210bce834166a789b95
Autor:
Xiaohu Qie, Zheng Wang, Jieping Ye, Li Zang, Xiaoqing Yang, Kung Fu, Huiting Hong, Lin Yucheng
Publikováno v:
KDD
The estimated time of arrival (ETA) is a critical task in the intelligent transportation system, which involves the spatiotemporal data. Despite a significant amount of prior efforts have been made to design efficient and accurate systems for ETA tas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ab5968d3b31809e6598d9a24e8bbde2
https://doi.org/10.1145/3394486.3403294
https://doi.org/10.1145/3394486.3403294
Publikováno v:
ICKG
Network embedding is an effective way to solve the network analytics problems such as node classification, link prediction, etc. It represents network elements using low dimensional vectors such that the graph structural information and properties ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e8632e1c4214553b99708bc43ea072a
https://doi.org/10.1109/icbk50248.2020.00024
https://doi.org/10.1109/icbk50248.2020.00024
Publikováno v:
ACM Transactions on Information Systems. 35:1-23
Recently, location-based services (LBSs) have been increasingly popular for people to experience new possibilities, for example, personalized point-of-interest (POI) recommendations that leverage on the overlapping of user trajectories to recommend P
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::106489fa99c0ae93bdf9dbc4e8b00994
https://doi.org/10.1145/3057283
https://doi.org/10.1145/3057283
Publikováno v:
AAAI
In this paper, we focus on graph representation learning of heterogeneous information network (HIN), in which various types of vertices are connected by various types of relations. Most of the existing methods conducted on HIN revise homogeneous grap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e6a55af70aefc93e9c2463c23e6964e
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-1
Network alignment is a critical task to a wide variety of fields. Many existing works leverage on representation learning to accomplish this task without eliminating domain representation bias induced by domain-dependent features, which yield inferio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03c2c0f5d0d7cae0f173c3164c15d7b3
https://doi.org/10.1109/tkde.2020.3023589
https://doi.org/10.1109/tkde.2020.3023589
Network embedding has become a hot research topic recently which can provide low-dimensional feature representations for many machine learning applications. Current work focuses on either (1) whether the embedding is designed as an unsupervised learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f8f5ef227ad24e98b7128783ec12713
Autor:
XIN LI1 xinli@bit.edu.cn, MINGMING JIANG1 jiangmings1992@163.com, HUITING HONG1 xhhszc@163.com, LEJIAN LIAO1 liaolj@bit.edu.cn
Publikováno v:
ACM Transactions on Information Systems. 2017, Vol. 35 Issue 4, p1-23. 23p.