Quality improvement methods are essential to gathering high-quality crowdsourced data,
both for research and industry applications. A popular and broadly applicable method is task …

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

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 …

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 …

Peer and self-assessment offer an opportunity to scale both assessment and learning to
global classrooms. This article reports our experiences with two iterations of the first large …

As a significant application of energy, smart grid is a complicated interconnected power grid
that involves sensors, deployment strategies, smart meters, and real-time data processing. It …

Recent approaches to crowdsourcing entity matching (EM) are limited in that they
crowdsource only parts of the EM workflow, requiring a developer to execute the remaining …

Crowdsourcing is widely accepted as a means for resolving tasks that machines are not
good at. Unfortunately, Crowdsourcing may yield relatively low-quality results if there is no …

A crowdsourcing system, such as the Amazon Mechanical Turk (AMT), provides a platform
for a large number of questions to be answered by Internet workers. Such systems have …