【学术报告】Trajectory-driven Influential Billboard Placement-西南科技大学计算机科学与技术学院
  • 【学术报告】Trajectory-driven Influential Billboard Placement
    2019-12-09 03:12:30      阅读:3136

    【报告时间】:2019年12月13日下午2:00

    【报告地点】:东6E206(计算机学院学术厅)

    【报告内容简介】:

    报告1(2:00-3:30):In this talk I will present our recent work on "Trajectory-driven Influential Billboard Placement" which is one of the Best Papers of KDD 2018. In this work we propose and study the problem of trajectory-driven influential billboard placement: given a set of billboards U (each with a location and a cost), a database of trajectories T and a budget L, find a set of billboards within the budget to influence the largest number of trajectories. One core challenge is to identify and reduce the overlap of the influence from different billboards to the same trajectories, while keeping the budget constraint into consideration. We show that this problem is NP-hard and present an enumeration based algorithm with (1 − 1/e) approximation ratio. However, the enumeration should be very costly when |U| is large. By exploiting the locality property of billboards’ influence, we propose a partition- based framework PartSel. PartSel partitions U into a set of small clusters, computes the locally influential billboards for each cluster, and merges them to generate the global solution. Since the local solutions can be obtained much more efficient than the global one, PartSel should reduce the computation cost greatly; meanwhile it achieves a non-trivial approximation ratio guarantee. Then we propose a LazyProbe method to further prune billboards with low marginal influence, while achieving the same approximation ratio as PartSel. Experiments on real datasets verify the efficiency and effectiveness of our methods. 

    报告2(4:00-5:00):如何做科研,作何做好高水平论文

    【报告人及简介】:

    zhifeng bao.png

    Zhifeng Bao is an Associate Professor in Computer Science, RMIT (Royal Melbourne Institute of Technology) University and an Honorary Senior Fellow at the University of Melbourne, Australia. His research interests include spatial data analytics, data visualization, and data integration. He received his PhD from the CS Dept at NUS in 2011. Zhifeng was the only recipient of the Best PhD Thesis Award in School of Computing and was the winner of the Singapore IDA (Infocomm Development Authority) gold medal. Zhifeng is a two-time winner of the Google Faculty Research Award 2015. He serves the Associate Editor of PVLDB Vol 14, and was the PC Co-chair of WSDM19 Cup, DASFAA17 (workshop track), ER18 (demo track), and the PC member of top conferences such as VLDB17-20, SIGMOD18, SIGIR15-19, ICDE16-20, WWW 18-19. Zhifeng has received five best paper awards such as KDD 2019 Best Paper Award Runnerup, DASFAA17 Best Student Paper Runnerup, and five best paper nominations such as KDD 2018, ICDE 2009, CIKM 2014. Please visit his homepage https://baozhifeng.net for more details.


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