Crowdsourced Data Management: A Survey

303 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective (2018, methodology): “Several surveys [82], [83], [84] cover these issues in detail.”
Toward a System Building Agenda for Data Integration (and Data Science) (2018, background): “Over the past few decades, DI has received much attention (e.g., [37, 29, 31, 20, 34, 33, 6, 17, 39, 22, 23, 5, 8, 36, 15, 35, 4, 25, 38, 26, 32, 19, 2, 12, 11, 16, 2, 3]).”
The ApolloScape Open Dataset for Autonomous Driving and Its Application (2018, background): “work flows of crowdsourcing object annotations [79], [80], [81], all our 2D/3D labeling tasks, e.”
Cleaning Crowdsourced Labels Using Oracles For Statistical Classification (2018, background): “This problem has been extensively studied in the crowdsourcing literature [23].”
Truth Inference in Crowdsourcing: Is the Problem Solved? (2017, background): “The database community has shown great interests in crowdsourcing (see a survey [29]).”
$\textsf{LoPub}$ : High-Dimensional Crowdsourced Data Publication With Local Differential Privacy (2016, background): “With the development of various integrated sensors and crowd sensing systems [19], crowdsourced information from all aspects can be collected and analyzed to better produce rich knowledge about the group, which can benefit everyone in the crowdsourced system [20].”