Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Yongshun Gong"'
Publikováno v:
PLoS ONE, Vol 18, Iss 3, p e0283365 (2023)
High utility sequential pattern (HUSP) mining aims to mine actionable patterns with high utilities, widely applied in real-world learning scenarios such as market basket analysis, scenic route planning and click-stream analysis. The existing HUSP min
Externí odkaz:
https://doaj.org/article/c2ed34d816194e0c8da55c75049582dd
Publikováno v:
ACM Transactions on Information Systems. 41:1-24
The prevalence of location-based services has generated a deluge of check-ins, enabling the task of human mobility understanding. Among the various types of information associated with the check-in venues, categories (e.g., Bar and Museum ) are vital
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:571-585
Nonoccurring behavior (NOB) studies have attracted the growing attention of scholars as a crucial part of behavioral science. As an effective method to discover both NOB and occurring behaviors (OB), negative sequential pattern (NSP) mining is succes
Many real-world problems deal with collections of data with missing values, e.g., RNA sequential analytics, image completion, video processing, etc. Usually, such missing data is a serious impediment to a good learning achievement. Existing methods t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9743cf769d68b735b971268f311762a
https://hdl.handle.net/10453/170362
https://hdl.handle.net/10453/170362
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:865-880
As a key mission of the modern traffic management, crowd flow prediction (CFP) benefits in many tasks of intelligent transportation services. However, most existing techniques focus solely on forecasting entrance and exit flows of metro stations that
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-17
Publikováno v:
IEEE Transactions on Multimedia. 24:1415-1425
Publikováno v:
2022 International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM).
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).