Yu Huang

selected publications

1. TKDE

   Snippet Policy Network for Multi-class Varied-length ECG Early Classification

   Huang, Yu, Yen, Gary G., and Tseng, Vincent S.

   IEEE Transactions on Knowledge and Data Engineering 2022

   Bib

   @article{huang2022spn,
     selected = {true},
     bibtex_show = {true},
     title = {Snippet Policy Network for Multi-class Varied-length ECG Early Classification},
     author = {Huang, Yu and Yen, Gary G. and Tseng, Vincent S.},
     journal = {IEEE Transactions on Knowledge and Data Engineering},
     year = {2022},
     abbr = {TKDE},
     publisher = {IEEE}
   }

2. TKDD

   Dynamic Graph Mining for Multi-Weight Multi-Destination Route Planning with Deadlines Constraints

   Huang, Yu, Ying, Josh Jia-Ching, Yu, Philip S., and Tseng, Vincent S.

   ACM Transactopms on Knowledge Discovery from Data 2021

   Abs Bib

   Route planning satisfied multiple requests is an emerging branch in the route planning field and has attracted significant attention from the research community in recent years. The prevailing studies focus only on seeking a route by minimizing a single kind of Travel Cost, such as trip time or distance, among others. In reality, most users would like to choose an appropriate route, neither fastest nor shortest route. Usually, a user may have multiple requirements, and an appropriate route would satisfy all requirements requested by the user. In fact, planning an appropriate route could be formulated as a problem of Multi-weight Multi-destination Route Planning with Deadlines Constraints (MWMDRP-DC). In this article, we propose a framework, namely, MWMD-Router, which addresses the MWMDRP-DC problem comprehensively. To consider the travel costs with time-variation, we propose not only four novel dynamic graph miner to extract travel costs that reveal users’ requirements but also two new algorithms, namely, Basic MWMD Route Planning and Advanced MWMD Route Planning, to plan a route that satisfies deadline requirements and optimizes another criterion like travel cost with time-variation efficiently. To the best of our knowledge, this is the first work on route planning that considers handling multiple deadlines for multi-destination planning as well as optimizing multiple travel costs with time-variation simultaneously. Experimental results demonstrate that our proposed algorithms deliver excellent performance with respect to efficiency and effectiveness.

   @article{10.1145/3412363,
     selected = {true},
     abbr = {TKDD},
     bibtex_show = {true},
     author = {Huang, Yu and Ying, Josh Jia-Ching and Yu, Philip S. and Tseng, Vincent S.},
     title = {Dynamic Graph Mining for Multi-Weight Multi-Destination Route Planning with Deadlines Constraints},
     year = {2021},
     issue_date = {February 2021},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     volume = {15},
     number = {1},
     issn = {1556-4681},
     url = {https://doi.org/10.1145/3412363},
     doi = {10.1145/3412363},
     journal = {ACM Transactopms on Knowledge Discovery from Data},
     articleno = {3},
     numpages = {32},
     keywords = {Route planning, multi-destination, trajectory data mining, deadline constraint}
   }