Task allocation is a major challenge in Mobile Crowd Sensing (MCS). While previous task
allocation approaches follow either the opportunistic or participatory mode, this paper …

With the rapid advancement of mobile devices and crowdsourcing platforms, spatial
crowdsourcing has attracted much attention from various research communities. A spatial …

With the popularity of smart devices and the development of high-speed wireless networks,
the spatial crowdsourcing has attracted much attention from both academia and industry (eg …

Faster and more cost-efficient, crowdsourced delivery is needed to meet the growing
customer demands of many industries, including online shop**, on-demand local delivery …

Due to the tremendous growth of online social networks in both participants and collected
contents, social data publication has provided an opportunity for numerous services …

Spatial Crowdsourcing (SC) is a novel platform that engages individuals in the act of
collecting various types of spatial data. This method of data collection can significantly …

Spatial crowdsourcing, a human-centric paradigm for performing spatial tasks, has drawn
rising attention. Task assignment and worker scheduling are basic issues in spatial …

Participant selection is a fundamental research issue in Mobile Crowdsensing (MCS).
Previous approaches commonly assume that adequately long periods of candidate …

Participant selection is a major research challenge in Mobile Crowdsensing (MCS).
Previous approaches commonly assume that adequately long and fixed periods of …

In a crowd market such as Amazon Mechanical Turk, the remuneration of Human
Intelligence Tasks is determined by the requester, for which they are not given many cues to …