With a growing interest in high-performing work teams and how to form them, a new
computational challenge, denominated Team Formation Problem (TFP), has emerged. After …

Many important data management and analytics tasks cannot be completely addressed by
automated processes. Crowdsourcing is an effective way to harness human cognitive …

Crowdsourcing has emerged as a novel problem-solving paradigm, which facilitates
addressing problems that are hard for computers, eg, entity resolution and sentiment …

Any important data management and analytics tasks cannot be completely addressed by
automated processes. These tasks, such as entity resolution, sentiment analysis, and image …

With the rapid development of mobile devices and crowdsourcing platforms, the spatial
crowdsourcing has attracted much attention from the database community. Specifically, the …

Crowdsourcing refers to solving large problems by involving human workers that solve
component sub-problems or tasks. In data crowdsourcing, the problem involves data …

Crowdsourcing has been shown to be effective in a wide range of applications, and is
seeing increasing use. A large-scale crowdsourcing task often consists of thousands or …

Crowdsourcing is a new computing paradigm that harnesses human effort to solve computer-
hard problems, such as entity resolution and photo tagging. The crowd (or workers) have …

Crowdsourcing systems provide a cost effective and convenient way to collect labels, but
they often fail to guarantee the quality of the labels. This paper proposes a novel framework …

Besides the simple human intelligence tasks such as image labeling, crowdsourcing
platforms propose more and more tasks that require very specific skills, especially in …