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SUMMARY:Spatial Crowdsourcing over Big Data\, Challenges and Opportunities
DTSTART:20140617T101500
DTSTAMP:20260407T011310Z
UID:bc3e84a0bd8fa451a4e70ecefc1ce555cfa880148b10b4645debdf92
CATEGORIES:Conferences - Seminars
DESCRIPTION:Lei CHEN\, The Hong Kong University of Science and Technology\
 , Hong Kong\nAs one of the successful forms of using Wisdom of Crowd\, cro
 wdsourcing\, has been widely used for many human intrinsic tasks\, such as
  image labeling\, natural language understanding\, market predication and 
 opinion mining. Meanwhile\, with advances in pervasive technology\, mobile
  devices\, such as mobile phones\, tablets\, and PDA\, have become extreme
 ly popular. These mobile devices can work as sensors to collect various ty
 pes of data\, such as pictures\, videos and texts. Therefore\, in crowdsou
 rcing\, a requester can unitize power of mobile devices and their location
  information to ask for resources related a specific location\, the mobile
  users who would like to take the task will travel to that place and get t
 he data (videos\, audios\, or pictures) and then send the data to the requ
 ester. This type of crowdsourcing is called spatial crowdsourcing. Due to 
 the rapid growth of mobile device uses and amazing functionality provided 
 by mobile devices\, spatial crowdsourcing will become more popular than ge
 neral crowdsourcing\, such as Amazon Turk and Crowdflower.\nIn this talk\,
  I will first briefly review the history of crowdsourcing and discuss the 
 key issues related to crowdsourcing. Then\, I will demonstrate the power o
 f spatial crowdsourcing with our recent developed software\, gMission. Fin
 ally\, I will highlight challenges and research opportunities about spatia
 l crowdsourcing over Big Data.
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
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