With the wide popularity of smart devices such as smartphones, smartwatches, and smart
cameras, Mobile Crowdsensing (MCS) and Crowdsourcing (CS) have been broadly applied …

Mobile crowdsensing (MCS) has recently found many applications in environmental
monitoring and large-scale surveillance by recruiting crowd workers for data collection and …

In mobile crowdsourcing (MCS), the platform selects participants to complete location-aware
tasks from the recruiters aiming to achieve multiple goals (eg, profit maximization, energy …

Mobile crowdsourcing (MCS) endeavors to attain reliable truth by recruiting large numbers
of users with handheld mobile devices to collect data. However, during the early stages of …

Crowdsensing has found a variety of applications (eg, spectrum sensing, environmental
monitoring) by leveraging the" wisdom" of a potentially large crowd of mobile users as" …

Mobile crowdsensing (MCS) depends on mobile users to collect sensing data, whose quality
highly depends on the expertise/experience of the users. It is critical for MCS to identify right …

Crowdsourcing is an important avenue for collecting machine learning data, but
crowdsourcing can go beyond simple data collection by employing the creativity and …

Microtask crowdsourcing has emerged as a cost-effective approach to collecting large-scale
high-quality labeled data across a wide range of business scenarios, particularly those …

Crowdsourcing is rapidly emerging as a computing paradigm that can employ the collective
intelligence of a distributed human population to solve a wide variety of tasks. However …

In mobile crowdsensing, finding the best match between tasks and users is crucial to ensure
both the quality and effectiveness of a crowdsensing system. Existing works usually assume …