Equipping machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

With the advancement in communication techniques and sensor technologies, mobile
crowdsensing (MCS)—one of the most successful applications of crowdsourcing—has …

Crowdsourcing is a computing paradigm where humans are actively involved in a
computing task, especially for tasks that are intrinsically easier for humans than for …

Cyberbullying is a growing problem across social media platforms, inflicting short and long-
lasting effects on victims. To mitigate this problem, research has looked into building …

Local administrations and governments aim at leveraging wireless communications and
Internet of Things (IoT) technologies to manage the city infrastructures and enhance the …

The rapid proliferation of online content producing and sharing technologies resulted in an
explosion of user-generated content (UGC), which now extends to scientific data. Citizen …

Spatial crowdsourcing (SC) is an emerging paradigm of crowdsourcing, which commits
workers to move to some particular locations to perform spatio-temporal-relevant tasks (eg …

Big data have the characteristics of enormous volume, high velocity, diversity, value-sparsity,
and uncertainty, which lead the knowledge learning from them full of challenges. With the …

Crowd intelligence tries to gather, process, infer, and ascertain massive useful information
by utilizing the intelligence of crowds or distributed computers, which has great potential in …

In spatial crowdsourcing, requesters submit their task-related locations and increase the
demand of a local area. The platform prices these tasks and assigns spatial workers to serve …