计算机软件新技术国家重点实验室
摘 要：
in this talk i will present our work as titled. in particular, we
study two common scenarios. goal 1 (our kdd18 work): maximize the number of
disintct users when influence overlap is considered - 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. goal 2 (our kdd19 work): maximize the influence for outdoor
advertising when impression counts are taken into consideration - in line with
the advertising consumer behavior studies, we adopt the logistic function to
take impression counts of a billboard to a user trajectory into consideration
when defining the influence measurement.
报告人简介:
zhifeng bao is an associate professor in
computer science, rmit (royal melbourne institute of technology) university and
an honorary fellow at the university of melbourne, australia. 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. his research interests include data
visualization, spatial data analytics
and data integration. he serves the associate editor of vldb 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 six
best paper nominations such as kdd 2018, icde 2009, cikm 2014. since 2015 he
has secured more than 1.5 million aud funding as the chief investigator from
australasian research council, csiro, google, etc.
时间：10月22日(星期二)14:00
地点：计算机科学技术楼230室
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