TY - GEN
T1 - Procrastination-aware scheduling
T2 - 35th IEEE International Conference on Data Engineering, ICDE 2019
AU - Wang, Libin
AU - Tong, Yongxin
AU - Hu, Chunming
AU - Chen, Lei
AU - Li, Yiming
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Procrastination is a prevalent form of self-control failure. As it often concerns with the individual's ability to meet the deadline, an efficient time management is crucial for overcoming it. Though a considerable amount of work in behavioral economics provides useful insights, there is not a computational way to guide us how to obtain an appropriate schedule for all the things to be done, especially when the relationship of the deadlines is intrinsic. In this paper, we first propose the Procrastination-aware Scheduling Problem (PSP) to model an appropriate schedule. A bipartite graph formulation is then developed to further illustrate the concepts. We find the PSP is NP-hard in the strong sense and design an approximation algorithm. In addition, we note the significance of the PSP under the online scenario (called OnlinePSP). Finally, we verify the effectiveness and efficiency of the proposed algorithms through extensive experiments on real datasets.
AB - Procrastination is a prevalent form of self-control failure. As it often concerns with the individual's ability to meet the deadline, an efficient time management is crucial for overcoming it. Though a considerable amount of work in behavioral economics provides useful insights, there is not a computational way to guide us how to obtain an appropriate schedule for all the things to be done, especially when the relationship of the deadlines is intrinsic. In this paper, we first propose the Procrastination-aware Scheduling Problem (PSP) to model an appropriate schedule. A bipartite graph formulation is then developed to further illustrate the concepts. We find the PSP is NP-hard in the strong sense and design an approximation algorithm. In addition, we note the significance of the PSP under the online scenario (called OnlinePSP). Finally, we verify the effectiveness and efficiency of the proposed algorithms through extensive experiments on real datasets.
KW - Bipartite graph
KW - Scheduling
UR - https://www.scopus.com/pages/publications/85067996619
U2 - 10.1109/ICDE.2019.00164
DO - 10.1109/ICDE.2019.00164
M3 - 会议稿件
AN - SCOPUS:85067996619
T3 - Proceedings - International Conference on Data Engineering
SP - 1650
EP - 1653
BT - Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PB - IEEE Computer Society
Y2 - 8 April 2019 through 11 April 2019
ER -