Information on the Qurk Project

Crowdsourcing platforms such as Amazon's Mechanical Turk make it possible to organize crowd workers to perform tasks like translation or image labelling on demand. Building these workflows is challenging: how much should you pay crowd workers? can you trust the output of each worker? how can you coordinate workers to perform complicated high-level tasks? Qurk helps you build crowd-powered data processing workflows using a PIG-like language while tackling these challenges on your behalf.

Professors:

• Sam Madden
• Rob Miller
• David Karger

Graduate Students:

• Adam Marcus
• Eugene Wu

Papers

• Crowdsourced Databases: Query Processing with People (CIDR 2011)
• Demonstration of Qurk: A Query Processor for Human Operators (SIGMOD 2011)
• Human-powered Sorts and Joins (VLDB 2012)

Screenshots from our VLDB 2012 paper for readability

• Figure 2(a) Simple Join
• Figure 2(b) Naive Batching
• Figure 2(c) Smart Batching
• Figure 5(a) Comparison Sort
• Figure 5(b) Rating Sort

E-mail us with questions.