Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Tsz Nam Chan"'
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::feb11bd736a7a7b97cedf365c4bb581e
https://doi.org/10.1109/tkde.2023.3253263
https://doi.org/10.1109/tkde.2023.3253263
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:4172-4185
Heterogeneous information networks (HINs), which are typed graphs with labeled nodes and edges, have attracted tremendous interest from academia and industry. Given two HIN nodes ${s}$ and ${t}$ , and a natural number ${k}$ , we study the discovery o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::966ba766d56b545159c46681fd921fdf
https://doi.org/10.1109/tkde.2020.3037218
https://doi.org/10.1109/tkde.2020.3037218
Publikováno v:
Proceedings of the VLDB Endowment. 15:3606-3609
Kernel density visualization (KDV) has been widely used in many geospatial analysis tasks, including traffic accident hotspot detection, crime hotspot detection, and disease outbreak detection. Although KDV can be supported by many scientific, geogra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::327b2e2e62623092fd0bccfbb626f2a0
https://doi.org/10.14778/3554821.3554855
https://doi.org/10.14778/3554821.3554855
Publikováno v:
Proceedings of the VLDB Endowment. 15:2853-2866
Network K -function has been the de facto operation for analyzing point patterns in spatial networks, which is widely used in many communities, including geography, ecology, transportation science, social science, and criminology. To analyze a locati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2535517bd771ac1d66e4804aba418e7a
https://doi.org/10.14778/3551793.3551836
https://doi.org/10.14778/3551793.3551836
Publikováno v:
Proceedings of the VLDB Endowment. 15:814-827
Spatial-temporal kernel density visualization (STKDV) has been extensively used in a wide range of applications, e.g., disease outbreak analysis, traffic accident hotspot detection, and crime hotspot detection. While STKDV can provide accurate and co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b0d55025979d7d9f9888bb6e5d8a9ce
https://doi.org/10.14778/3503585.3503591
https://doi.org/10.14778/3503585.3503591
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 31:4293-4304
The multi-exposure fusion (MEF) methods have received much attention in recent years due to the importance of constructing high dynamic range images. Among most of the existing studies, multi-scale structural-patch-decomposition-based MEF (MSPD-MEF)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec32ecdec09cc264bd98ce100788e478
https://doi.org/10.1109/tcsvt.2021.3053405
https://doi.org/10.1109/tcsvt.2021.3053405
Publikováno v:
Proceedings of the VLDB Endowment. 15:513-526
Kernel density visualization (KDV) has been the de facto method in many spatial analysis tasks, including ecological modeling, crime hotspot detection, traffic accident hotspot detection, and disease outbreak detection. In these tasks, domain experts
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc9a0660bdd554153bef2db501a2a7df
https://doi.org/10.14778/3494124.3494135
https://doi.org/10.14778/3494124.3494135
Publikováno v:
Proceedings of the VLDB Endowment. 14:2655-2658
Kernel density visualization (KDV) is a commonly used visualization tool for many spatial analysis tasks, including disease outbreak detection, crime hotspot detection, and traffic accident hotspot detection. Although the most popular geographical in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ccc32e3ff2ed87a0e375eebe621bde99
https://doi.org/10.14778/3476311.3476312
https://doi.org/10.14778/3476311.3476312
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::002724609e6806e78023fcc9e393e25b
https://doi.org/10.1109/icde53745.2022.00233
https://doi.org/10.1109/icde53745.2022.00233
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::162c80b1ad65575cdb8a90d57d479591
https://doi.org/10.1109/icde53745.2022.00014
https://doi.org/10.1109/icde53745.2022.00014